Political Participation and the Media -...

1

Political Participation and the Media Technical Appendix 9/14/2016 BBC Media Action Andrea Scavo

2

Contents

Contents ................................................................................................................................................... 2

List of Tables ............................................................................................................................................. 3

List of Figures ............................................................................................................................................ 5

1 The sample ........................................................................................................................................ 6

2 Building the construct variables ........................................................................................................... 7

2.1 Factor analysis of construct variables........................................................................................... 8 2.1.1 Participation ...................................................................................................................... 8 2.1.2 Knowledge ...................................................................................................................... 10 2.1.3 Discussion ....................................................................................................................... 13 2.1.4 Efficacy ............................................................................................................................ 14

3 Bivariate analysis .............................................................................................................................. 17

3.1 Exposure – outcome variables .................................................................................................. 17 3.1.1 Exposure variable ............................................................................................................ 17 3.1.2 Outcome variables ........................................................................................................... 18 3.1.3 Results ............................................................................................................................ 19

3.2 Outcome variables’ correlation ................................................................................................. 20

3.3 Exposure – confounders........................................................................................................... 21 3.3.1 Description of confounders .............................................................................................. 21 3.3.2 Exposure and categorical variables .................................................................................... 24 3.3.3 Exposure and ordinal variables .......................................................................................... 27

3.4 Outcome variables – confounders ............................................................................................. 27 3.4.1 Participation .................................................................................................................... 27 3.4.2 Knowledge ...................................................................................................................... 30 3.4.3 Discussion ....................................................................................................................... 33 3.4.4 Efficacy ............................................................................................................................ 36

4 Multivariate regression analysis ......................................................................................................... 40

4.1 Regression models – Participation ............................................................................................. 42 4.1.1 Model n. 1 – Exposure with all confounders ...................................................................... 42 4.1.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 44 4.1.3 Model n. 3 – Exposure & significant interactions ................................................................ 47 4.1.4 Model n. 4 – Exposure & Country interactions .................................................................. 50

4.2 Regression models – Knowledge ............................................................................................... 54 4.2.1 Model n. 1 – Exposure with all confounders ...................................................................... 54 4.2.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 56 4.2.3 Model n. 3 – Exposure & significant interactions ................................................................ 59 4.2.4 Model n. 4 – Exposure & Country interactions .................................................................. 62

4.3 Regression models – Discussion ............................................................................................... 66 4.3.1 Model n. 1 – Exposure with all confounders ...................................................................... 66 4.3.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 68 4.3.3 Model n. 3 – Exposure & significant interactions ................................................................ 71 4.3.4 Model n. 4 – Exposure & Country interactions .................................................................. 74

4.4 Regression models – Efficacy .................................................................................................... 78 4.4.1 Model n. 1 – Exposure with all confounders ...................................................................... 78 4.4.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 80 4.4.3 Model n. 3 – Exposure & significant interactions ................................................................ 83 4.4.4 Model n. 4 – Exposure & Country interactions .................................................................. 86

3

List of Tables Table 1: Data collection and Sample size by country ............................................................................................................ 6

Table 2 - Construct variables and original items .................................................................................................................... 7

Table 3 - Reliability test and Factor Analysis, Participation ................................................................................................. 9

Table 4 - Descriptives of Participation ...................................................................................................................................... 9

Table 5 - Reliability test and Factor Analysis, Knowledge (Bangladesh) ......................................................................... 10

Table 6 - Reliability test and Factor Analysis, Knowledge (Nepal)................................................................................... 11

Table 7 - Reliability test and Factor Analysis, Knowledge (Kenya) .................................................................................. 11

Table 8 - Reliability test and Factor Analysis, Knowledge (Nigeria) ................................................................................ 11

Table 9 - Reliability test and Factor Analysis, Knowledge (Tanzania) ............................................................................. 12

Table 10 - Reliability test and Factor Analysis, Knowledge (Sierra Leone).................................................................... 12

Table 11 - Reliability test and Factor Analysis, Knowledge (Myanmar) .......................................................................... 12

Table 12 - Descriptives of Knowledge .................................................................................................................................... 13

Table 13 - Reliability test and Factor Analysis, Discussion ................................................................................................. 14

Table 14 - Descriptives of Discussion ..................................................................................................................................... 14

Table 15 - Reliability test and Factor Analysis, Efficacy ....................................................................................................... 15

Table 16 - Descriptives of Efficacy ............................................................................................................................................ 15

Table 17 - List of BBC Media Action Governance debate/magazine programmes by country ................................ 18

Table 18 - Distribution of frequencies, Exposure................................................................................................................. 18

Table 19 - T-test results, Exposure - Participation .............................................................................................................. 19

Table 20 - T-test results, Exposure - Knowledge ................................................................................................................. 19

Table 21 - T-test results, Exposure - Discussion .................................................................................................................. 20

Table 22 - T-test results, Exposure - Efficacy ........................................................................................................................ 20

Table 23 - Outcomes' correlation matrix............................................................................................................................... 21

Table 24 - Distribution of frequencies, Gender .................................................................................................................... 21

Table 25 - Distribution of frequencies, Age ........................................................................................................................... 22

Table 26 - Distribution of frequencies, Location .................................................................................................................. 22

Table 27 - Distribution of frequencies, Education ................................................................................................................ 22

Table 28 - Distribution of frequencies, Income .................................................................................................................... 23

Table 29 - Distribution of frequencies, Marital status ......................................................................................................... 23

Table 30 - Distribution of frequencies, Interest .................................................................................................................... 24

Table 31 - Distribution of frequencies, Group activity ....................................................................................................... 24

Table 32 - Cross-tabulation and Chi-Square test, Exposure by Gender ........................................................................ 24

Table 33 - Cross-tabulation and Chi-Square test, Exposure by Location ...................................................................... 25

Table 34 - Cross-tabulation and Chi-Square test, Exposure by Group activity ........................................................... 25

Table 35 - Cross-tabulation and Chi-Square test, Exposure by Country ...................................................................... 26

Table 36 - Cross-tabulation and Chi-Square test, Exposure by Marital status ............................................................. 26

Table 37 - Significance testing for Exposure and ordinal variables ................................................................................... 27

Table 38 - T-test results, Gender - Participation.................................................................................................................. 27

Table 39 - T-test results, Location - Participation ................................................................................................................ 28

Table 40 - T-test results, Group activity - Participation ..................................................................................................... 28

Table 41 - ANOVA for Participation, by Country ............................................................................................................... 29

Table 42 - ANOVA for Participation, by Marital Status ..................................................................................................... 29

Table 43 - Correlation coefficients for Participation and ordinal variables ................................................................... 30

Table 44 - T-test results, Gender - Knowledge .................................................................................................................... 30

Table 45 - T-test results, Location - Knowledge .................................................................................................................. 31

Table 46 - T-test results, Group activity - Knowledge ....................................................................................................... 31

Table 47 - ANOVA for Knowledge, by Country .................................................................................................................. 32

Table 48 - ANOVA for Knowledge, by Marital Status ........................................................................................................ 32

Table 49 - Correlation coefficients for Knowledge and ordinal variables ...................................................................... 33

Table 50 - T-test results, Gender - Discussion ..................................................................................................................... 33

Table 51 - T-test results, Location - Discussion ................................................................................................................... 34

Table 52 - T-test results, Group activity - Discussion ........................................................................................................ 34

Table 53 - ANOVA for Discussion, by Country................................................................................................................... 35

Table 54 - ANOVA for Discussion, by Marital Status ......................................................................................................... 35

Table 55 - Correlation coefficients for Discussion and ordinal variables....................................................................... 36

Table 56 - T-test results, Gender - Efficacy ........................................................................................................................... 36

4

Table 57 - T-test results, Location - Efficacy ......................................................................................................................... 37

Table 58 - T-test results, Group activity - Efficacy ............................................................................................................... 37

Table 59 - ANOVA for Efficacy, by Country ......................................................................................................................... 38

Table 60 - ANOVA for Efficacy, by Marital Status ............................................................................................................... 38

Table 61 - Correlation coefficients for Efficacy and ordinal variables ............................................................................. 39

Table 62 - List of regression models ........................................................................................................................................ 41

Table 63 - Model n. 1 summary - Participation ..................................................................................................................... 42

Table 64 – Model n. 1 ANOVA - Participation ..................................................................................................................... 42

Table 65 - Model n. 1 regression coefficients - Participation ............................................................................................ 43

Table 66 - Model n. 1 diagnostics - Participation .................................................................................................................. 43


Table 68 - Model n. 2 ANOVA - Participation ...................................................................................................................... 45











Table 79 - Model n. 1 summary - Knowledge ....................................................................................................................... 54

Table 80 - Model n. 1 ANOVA - Knowledge ........................................................................................................................ 54

Table 81 - Model n. 1 regression coefficients - Knowledge ............................................................................................... 55

Table 82 - Model n. 1 diagnostics - Knowledge .................................................................................................................... 55













Table 95 - Model n. 1 summary - Discussion ........................................................................................................................ 66

Table 96 - Model n. 1 ANOVA - Discussion ......................................................................................................................... 66

Table 97 - Model n. 1 regression coefficients - Discussion ................................................................................................ 67

Table 98 - Model n. 1 diagnostics - Discussion ..................................................................................................................... 67

Table 99 - Model n. 2 summary - Discussion ........................................................................................................................ 68

Table 100 - Model n. 2 ANOVA - Discussion ....................................................................................................................... 69

Table 101 - Model n. 2 regression coefficients - Discussion ............................................................................................. 70

Table 102 - Model n. 2 diagnostics - Discussion ................................................................................................................... 70

Table 103 - Model n. 3 summary - Discussion ...................................................................................................................... 71




Table 107 - Model n. 4 summary - Discussion ...................................................................................................................... 74




Table 111 - Model n. 1 summary - Efficacy ............................................................................................................................ 78

Table 112 - Model n. 1 ANOVA - Efficacy ............................................................................................................................. 78

Table 113 - Model n. 1 regression coefficients - Efficacy .................................................................................................... 79

Table 114 - Model n. 1 diagnostics - Efficacy ......................................................................................................................... 79

5













List of Figures Figure 1 - Distribution of frequencies, Participation ............................................................................................................ 10

Figure 2 - Normal Q-Q plot, Participation............................................................................................................................. 10

Figure 3 - Distribution of frequencies, Knowledge .............................................................................................................. 13

Figure 4 - Normal Q-Q plot, Knowledge ............................................................................................................................... 13

Figure 5 - Distribution of values, Discussion ......................................................................................................................... 14

Figure 6 - Normal Q-Q plot, Discussion ................................................................................................................................ 14

Figure 7 - Distribution of frequencies, Efficacy ...................................................................................................................... 16

Figure 8 - Normal Q-Q plot, Efficacy ...................................................................................................................................... 16

Figure 9 - Residuals and predicted values - Model n. 1 - Participation ........................................................................... 44

Figure 10 - Residuals and predicted values - Model n. 2 - Participation ......................................................................... 47



Figure 13 - Residuals and predicted values - Model n. 1 - Knowledge............................................................................ 56




Figure 17 - Residuals and predicted values - Model n. 1 - Discussion............................................................................. 68




Figure 21 - Residuals and predicted values - Model n. 1 - Efficacy ................................................................................... 80




6

TECHNICAL APPENDIX

This appendix details the processes used to construct the models that have produced the results

presented in the main report. First, data used in the analysis are discussed, describing how they were

collected and modelled for the analysis. Second, the process of deriving the construct variables (i.e.

Participation, Knowledge, Discussion, and Efficacy) through Exploratory Factor Analysis is detailed.

Third, the bivariate analysis methods employed for the analysis of the relationships between

exposure to BBC Governance programming and those construct variables are presented and

discussed. Finally, the regression models for the multivariate analysis of the same relationships, while

controlling for socio-political and demographic confounders, are discussed.

1 The sample

This research is based on multi-country, cross-national data. All data were collected through primary

research carried out by BBC Media Action. All the analyses were conducted on a single dataset of

23621 cases, collected across seven countries at various points in time: Bangladesh, Nepal, Kenya,

Nigeria, Tanzania, Sierra Leone, and Myanmar. Where multiple phases of data collection were

carried out, only the most recent single dataset from each country was incorporated into the

composite dataset.

Table 1: Data collection and Sample size by country

Country Data Collection Sample size

Bangladesh July 2015 2650

Myanmar August 2013 1224

Nepal January 2016 4000

Kenya January 2015 3003

Nigeria December 2014 4240

Sierra Leone July 2013 4389

Tanzania August 2013 4114

Data were originally collected for analysis at national level. Therefore, we needed to merge seven

different datasets and to check for consistency of the variables across countries. This is because

there were slight differences in the way questions were asked to respondents, due to cultural and

linguistic differences across countries. Some questions were asked differently from one country to

another, while others were not asked at all in some countries. Therefore, we needed to select for

the analysis only those variables that were consistently measured across countries, leaving out of the

analysis potentially relevant variables that were not measured in all countries (such as disability –

which was measured only in Bangladesh, Kenya and Nigeria – and trust in political institutions –

which was not measured in Nepal and Myanmar).

Samples are representative of national adult population (15+) in all of the seven countries. Our

sampling approach is random, self-weighting in all countries1. Samples are stratified for region (or

1 We applied Probability Proportional to Size (PPS) sampling for selection of districts, wards and villages,

ensuring that strata’s population proportions fall within 95% confidence intervals around sample’s proportions

in all cases.

7

other intra-country administrative sub-divisions) and urban/rural location. For these reasons we did

not weight the data.

2 Building the construct variables

This section details the process undertaken to derive construct variables, considered as outcomes in

the analysis. We define as construct variables all those variables that we did not measure directly

in our surveys but that we derived from other variables measured directly (referred to as items).

See Table 2 for a list of the construct variables together with the items they were derived from.

Table 2 - Construct variables and original items

CONSTRUCT ITEMS LABEL ORIGINAL VALUES

PARTICIPATION

ParticipationA Participation - In an organised effort to

solve a neighbourhood or community

problem

0 – Not done

1 – Done once

2 – Done several times

ParticipationB Participation - Attended a meeting of the

local town council

ParticipationC Participation - Contacted a local official

ParticipationD Participation - Contacted a national

elected official

ParticipationE Participation - Contacted a local chief or

traditional leader about an issue

ParticipationF Participation - Taken part in a protest,

march, or demonstration

VotingA Voting - Likelihood to vote to next

general elections 0 – Very unlikely

1 – Somewhat unlikely

2 – Somewhat likely

3 – Very likely VotingB

Voting - Likelihood to vote to next local

elections

KNOWLEDGE

- depending on

country

specificities2

0 – Nothing at all

1 – Not very much

2 – A fair amount

3 – A great deal

DISCUSSION

DiscussionA Discussion - Frequency with family

members 0 – Never

1 – Occasionally

2 - Frequently

DiscussionB Discussion - Frequency with with friends

DiscussionC Discussion - Frequency with people

outside family and friends

EFFICACY

EmpowermentA Empowerment - Entitlement to question

0 – Strongly disagree

1 – Disagree

2 – Agree

3 – Strongly agree

EmpowermentB Empowerment - There are ways to

question

EmpowermentC Empowerment - Satisfied with the current

account politicians give

ExtEfficacyA ExtEfficacy - Government listens when

people get together

ExtEfficacyC ExtEfficacy - National government acts on

the need of ordinary people

We adopted the same approach for deriving each one of the construct variables. Firstly, we selected

a list of items that were:

- related to the concept the construct variable is meant to measure, according to the relevant

literature on the subject and to previous BBC Media Action’s research3;

2 Refer to specific country tables below (Tables 5 – 11).

8

- available in all national datasets.

Secondly, when needed, we recoded the items in order to have a homogeneous measure across

countries. This included re-scaling items (e.g. from four-point to three-point scales), since original

measures were not homogeneous across countries.

Thirdly, we ran Exploratory Factory Analysis, aiming at checking the consistency among the original

items and their correlation with the factor(s) extracted and, therefore, refining the list of original

items for each construct. We looked at Standardised Cronbach’s Alpha, Kaiser-Meyer-Olkin

Measure of Sampling Adequacy, the proportion of items’ variance explained by the factor(s), and the

factor loadings to evaluate the goodness of the different possible factors structures. Following

convention, we considered:

- a minimum threshold of 0.5 for Standardised Cronbach’s Alpha;

- a minimum threshold of 0.6 for Kaiser-Meyer-Olkin Measure of Sampling Adequacy;

- a minimum threshold of 40% of explained variance;

- a minimum of 0.4 for each item’s factor loading4.

Where possible, we aimed at identifying one single factor through Principal Axis Factoring extraction

method (since items’ distributions were not normal in most cases).

Fourthly, we checked if the preferred factor solutions hold consistently across countries, by running

Confirmatory Factor Analysis in each national dataset with the identified solutions.

Fifthly, once we obtained a refined list of original items that load well enough into the single

construct, we computed a simple average of their scores in order to have a single measure of the

construct.

Sixthly and finally, we re-scaled the construct’s value to a 0 to 10 scale for comparability purposes.

2.1 Factor analysis of construct variables

2.1.1 Participation

Exploratory Factor Analysis of eight observed variables allows us to identify “Political Participation”

as a single latent variable, explaining more than one third of the total variance5.

Based on 20631 valid cases (87.3% of total) the Cronbach's Alpha is 0.746, which means the

consistency among items is quite high.

3 See, for example, “How do debate programmes influence knowledge of key governance issues and political

participation?” (available at www.bbc.co.uk/mediaaction/publications-and-

resources/research/briefing/africa/sierra-leone/governance) and “How do political debate programmes

influence political participation? A case study from Nepal” (available at

www.bbc.co.uk/mediaaction/publications-and-resources/research/reports/asia/nepal/research-nepal-debate-

political-participation). 4 Single exceptions to these rules of thumb will be discussed in the detailed description of each construct

below. 5 This is the only case in which the explained variance is below the 40% threshold. However, considering the

relatively high number of items (8) this is acceptable.

9

Sample adequacy is tested both with a KMO Measure (that is 0.718) and a Bartlett's Test of

Sphericity, which proved to be extremely significant (<0.001).

Participation is particularly related to ParticipationB (Attended a meeting of the local town council).

In the case of ParticipationF (Taken part in a protest, march, or demonstration) the factor loading is

below the 0.4 threshold. However, this is understandable since this form of participation is often

negatively perceived, especially in less democratic countries.

Table 3 - Reliability test and Factor Analysis, Participation

CONSTRUCT ITEMS LABEL FACTOR

LOADINGS

PARTICIPATION

ParticipationA Participation - In an organised effort to solve a neighbourhood or

community problem 0.605

ParticipationB Participation - Attended a meeting of the local town council 0.695

ParticipationC Participation - Contacted a local official 0.674

ParticipationD Participation - Contacted a national elected official 0.551

ParticipationE Participation - Contacted a local chief or traditional leader about an

issue 0.597

ParticipationF Participation - Taken part in a protest, march, or demonstration 0.358

VotingA Voting - Likelihood to vote to next general elections 0.445

VotingB Voting - Likelihood to vote to next local elections 0.426

CRONBACH'S

ALPHA KMO N

BARTLETT TEST

(α=0.01) EIGENVALUE % OF VAR.

Χ2 df p-value

0.746 0.718 20631 62034.795 28 <0.001 2.997 37.5%

The distribution of frequencies for Participation is somewhat positively skewed, while it may be

considered mesokurtic. As the Normal Q-Q plot shows, the distribution is close to normality.

Table 4 - Descriptives of Participation

N Valid 23590

Missing 31

Mean 3.7157

Median 3.1250

Std. Deviation 2.08847

Skewness .740

Std. Error of Skewness .016

Kurtosis .186

Std. Error of Kurtosis .032

10

2.1.2 Knowledge

As already stated in the introduction of this section, we derived this construct variable through a

partially different process. Since questions on self-reported level of knowledge necessarily needed to

be related to countries’ specific political agendas, it was not possible to ask respondents a

predetermined set of questions. Therefore, the questions actually asked vary from one country to

another. Nonetheless, data are still comparable since the rationale of the questions’ selection was

consistent across countries. Questions relate to, indeed, the topics mainly covered by BBC Media

Action Governance programming, which are in turn selected from amongst the most relevant issues

in the public and political debate in each country.

The tables below report the main results of the reliability test and the factor analysis for each

country, also specifying which topics were covered in each country’s questions on self-reported

political knowledge.

In all cases the relevant parameters are above the defined thresholds (as they are defined at page 8).

Table 5 - Reliability test and Factor Analysis, Knowledge (Bangladesh)

COUNTRY LABEL FACTOR

LOADINGS

Bangladesh

Recent violence and hartal strikes/blockades following the general election in 2014 0.814

Demand for more discussion between government and the opposition to end the

current political unrest 0.833

Leaking of questions from public exams (e.g. SSC, HSC, BCS) 0.697

Decisions of the war crime tribunal and issuing of death penalties 0.841

CRONBACH'S

ALPHA KMO N

BARTLETT TEST (α=0.01) EIGENVALUE % OF VAR.

Χ2 df p-value

0.873 0.811 2301 4742.747 6 <0.001 2.903 72.6%

Figure 1 - Distribution of frequencies, Participation Figure 2 - Normal Q-Q plot, Participation

11

Table 6 - Reliability test and Factor Analysis, Knowledge (Nepal)


LOADINGS

Nepal

The new constitution 0.596

The Government’s response to the earthquake and the aftermath 0.65

Dalit issues 0.752

Gender issues 0.747

Employment 0.813

Migrant issues 0.773

Development issues 0.783

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.889 0.902 3561 12394.2 21 <0.001 4.218 60.3%

Table 7 - Reliability test and Factor Analysis, Knowledge (Kenya)


LOADINGS

Kenya

The new constitution 0.596

Employment 0.813

Migrant issues 0.773

Development issues 0.783

CRONBACH'S

ALPHA KMO N

BARTLETT TEST (α=0.01) EIGENVALUE % OF VAR.

Χ2 df p-value

0.768 0.777 2784 2675.439 6 <0.001 2.359 59.0%

Table 8 - Reliability test and Factor Analysis, Knowledge (Nigeria)


LOADINGS

Nigeria

Corruption in government 0.804

Ethnic related conflicts 0.759

Poor delivery of public services 0.788

The national budget 0.714

Inequality between women and men 0.69

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.866 0.852 4048 9114.03 10 <0.001 3.258 65.2%

12

Table 9 - Reliability test and Factor Analysis, Knowledge (Tanzania)


LOADINGS

Tanzania

Maternal health 0.593

Access to clean water 0.761

Health infrastructure 0.844

Transport infrastructure 0.774

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.83 0.782 3992 6234.79 6 <0.001 2.658 66.5%

Table 10 - Reliability test and Factor Analysis, Knowledge (Sierra Leone)


LOADINGS

Sierra Leone

Women’s rights 0.742

Political party agendas 0.808

Water and electricity service delivery 0.675

Corruption 0.733

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.828 0.789 3725 5434.99 6 <0.001 2.641 66.0%

Table 11 - Reliability test and Factor Analysis, Knowledge (Myanmar)


LOADINGS

Myanmar

New foreign company investments in Myanmar 0.746

The Kachin conflict and peace negotiations 0.746

Crisis in Rakhine and Meikhtila 0.736

Efforts to reduce corrpution within government 0.706

Ethnic and religious diversity of Myanmar 0.696

Opportunities for volunteering and participating in your community 0.542

Individual economic and employment rights 0.644

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.863 0.871 971 2771.62 21 <0.001 3.854 55.1%

The distribution of Knowledge values is substantially symmetric, although a bit platykurtic.

Nonetheless, we may consider it close to normality, as the Normal Q-Q plot shows.

13

Table 12 - Descriptives of Knowledge

N Valid 23030

Missing 591

Mean 4.7725

Median 5.0010


Skewness -.090


Kurtosis -.567


2.1.3 Discussion

Exploratory Factor Analysis of three observed variables allows us to identify “Discussion” as a single

latent variable, explaining roughly two thirds of the total variance.

Based on no. 22871 valid cases (96.8% of total) the Cronbach's Alpha is 0.758, which means the

consistency among items is quite high.

Sample adequacy is tested both with a KMO Measure (that is 0.676) and a Bartlett's Test of

Sphericity, which proved to be extremely significant (<0.001).

Discussion is particularly related to DiscussionB (Frequency with friends).

Figure 3 - Distribution of frequencies, Knowledge Figure 4 - Normal Q-Q plot, Knowledge

14

Table 13 - Reliability test and Factor Analysis, Discussion


LOADINGS

DISCUSSION

DiscussionA Discussion - Frequency with family members 0.661

DiscussionB Discussion - Frequency with friends 0.837

DiscussionC Discussion - Frequency with people outside family and friends 0.652

CRONBACH'S

ALPHA KMO N

BARTLETT TEST


Χ2 df p-value

0.758 0.676 22871 17269.314 3 <0.001 2.022 67.4%

The distribution of Discussion is practically symmetric, while it is somewhat platykurtic. However,

also in this case the Normal Q-Q plot, we can consider this distribution close to normality.

Table 14 - Descriptives of Discussion

N Valid 23398

Missing 223

Mean 4.5404

Median 5.0010


Skewness .049


Kurtosis -.705


2.1.4 Efficacy

Exploratory Factor Analysis of five observed variables allows us to identify “Efficacy” as a single

latent variable, explaining roughly almost half of the total variance.

Figure 5 - Distribution of values, Discussion Figure 6 - Normal Q-Q plot, Discussion

15

Based on no. 17918 valid cases (75.9% of total) the Cronbach's Alpha is 0.635, which means the

consistency among items is not as high as in the cases of Participation, Discussion, and the

Knowledge constructs, but it is still acceptable since well above the 0.5 threshold.

Sample adequacy is tested both with a KMO Measure (0.667) and a Bartlett's Test of Sphericity,

which proved to be extremely significant (<0.001).

Efficacy is moderately related to all of the five original items, ranging from EmpowermentA

(Entitlement to question), whose loading is 0.495, and ExtEfficacyC (National government acts on

the need of ordinary people), whose loading is 0.63.

Table 15 - Reliability test and Factor Analysis, Efficacy


LOADINGS

EFFICACY

EmpowermentA Empowerment - Entitlement to question 0.495

EmpowermentB Empowerment - There are ways to question 0.562

EmpowermentC Empowerment - Satisfied with the current account politicians give 0.511

ExtEfficacyA ExtEfficacy - Government listens when people get together 0.506

ExtEfficacyC ExtEfficacy - National government acts on the need of ordinary people

0.63

CRONBACH'S ALPHA

KMO N BARTLETT TEST (α=0.01)

EIGENVALUE % OF VAR. Χ

2 df p-value

0.635 0.667 17918 8120.907 6 <0.001 1.857 46.4%

Efficacy appears to be distributed normally. Both skewness and kurtosis values are relatively close to

0, and the Normal Q-Q plot shows that the distribution is close to normality.

Table 16 - Descriptives of Efficacy

N Valid 23126

Missing 495

Mean 5.4333

Median 5.3333


Skewness -.135


Kurtosis .244


16

Figure 7 - Distribution of frequencies, Efficacy Figure 8 - Normal Q-Q plot, Efficacy

17

3 Bivariate analysis

This section describes the analysis we conducted in order to measure the strength and the direction

of bivariate relationships between pairs of variable involved in this study, as well as to test their

significance.

More precisely, we analysed:

- the relationship between our main independent variable, Exposure, and the construct

variables we defined as outcomes (Participation, Discussion, Knowledge and Efficacy);

- the relationships among outcome variables;

- the relationship between Exposure and all the socio-demographic variables potentially

associated to it (referred to as “confounders”);

- the relationship between our outcome variables and confounders.

We conducted different types of significance test, according to the nature of the variables

considered. T-tests for means difference, Mann-Whitney U-tests, Pearson’s R and Spearman’s Rho

correlation coefficients and Chi-squared significance tests were conducted to test the association of

each pair of variable. All significance tests were conducted with α = 0.01.

The following sections report the parameters and the results of the significance testing for all of the

relationships analysed.

3.1 Exposure – outcome variables

3.1.1 Exposure variable

Exposure is a binary variable, derived from a set of questions about awareness of BBC Media Action

Governance programming6, recentness of last listening to / watching the programme, and frequency

of listening/watching. Therefore, we defined:

- Non-reached people as those who have not listened to / watched any BBC Media Action

governance programme during the last 12 months;

- Reached people as those who are aware of at least one BBC Media Action governance

programme and have listened to / watched it during the last 12 months;

- Regularly reached people as those who are aware of at least one BBC Media Action

governance programme and have listened to / watched it during the last 12 months, and

have listened to / watched every other episode (at least);

- Media dark people as those who have not accessed any relevant media during the last 12

months.

6 In this research we specifically considered only BBC Media Action programmes that have a talk or debate

format. For a list of the actual programmes, see Table 17.

18

Table 17 - List of BBC Media Action Governance debate/magazine programmes by country

Country Programme Format Platform Since

Bangladesh Sanglap Debate TV/Radio

2005 (3rd series started

2012)

Myanmar Lin Lait Kyair Sin Magazine Radio 2011

Current Affairs Debate TV 2014

Lively News Magazine Radio

Kenya Sema Kenya Debate TV 2012

Nepal Sajha Sawal Debate TV 2007

Nigeria GGK Magazine Radio 2013 (after 2 years off air)

Sierra Leone Fo Rod Magazine Radio 2011

Tok Bot Salone Debate Radio 2012

Tanzania Haba Na Haba Magazine Radio

In our analysis, we set ‘reached (but not regularly)’ and ‘media dark’ respondents as missing cases,

since we want to detect the ‘effect’ of full exposure to the programmes on our potential audience.

Therefore, the Exposure variable assumes a “0” value for not reached respondents and “1” for those

who are regularly reached by at least one programme (in case there is more than one programme

broadcasted in their country, as in the case of Myanmar or Sierra Leone).

Table 18 - Distribution of frequencies, Exposure

Exposure to at least one governance programme

Frequency Percent Valid Percent Cumulative Percent

Valid

Not reached 15875 67.2 80.8 80.8

Regularly reached 3778 16.0 19.2 100.0

Total 19653 83.2 100.0

Missing

Reached (but not regularly) 1176 5.0 Media dark 2792 11.8 Total 3968 16.8

Total 23621 100.0

3.1.2 Outcome variables

As described in Section 2 of this Technical Appendix, we derived all of the outcome variables

constructs from several original items. For each construct, we re-scaled the average score of the

original items into a 0-10 scale in order to have comparable measures of our dependent variables.

See Tables 4, 6, 14, and 16, and Figures 1-4 for each variable’s main descriptive parameters and

distributions of frequencies.

19

3.1.3 Results

Exposure is significantly and positively associated with all of the outcome variables except Efficacy.

Exposed people report higher Participation (+0.99), Discussion (+1.24), and Knowledge (+1.34)

scores. The difference between exposed and unexposed people in Efficacy scores is very little (0.05)

and not significant.

In all cases the assumption of equal variances in the two groups is not met according to the Levene’s

test. Therefore, we conducted a Welch’s t-test to test the significance of mean differences.

Due to the large size of the sample, the significance level has been set at 0.01.

Table 19 - T-test results, Exposure - Participation

Exposure to at least one

governance programme N Mean

Std.

Deviation

Std.

Error

Mean

Average

political

participation

(0 to 10)

Regularly

reached 3778 4.5323 2.23057 .03629

Not reached 15869 3.5381 2.00155 .01588

Levene's Test for

Equality of

Variances

t-test for Equality of Means

F Sig. t df Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed 166.297 < 0.001

26.830 19645 < 0.001 .99412 .03705 .89868 1.08957

Equal

variances not

assumed

25.096 5315.742 < 0.001 .99412 .03961 .89205 1.09620

Table 20 - T-test results, Exposure - Knowledge



Std.

Deviation

Std. Error

Mean

Average Self-

reported

knowledge (0

to 10)

Regularly

reached 3761 5.9344 2.24430 .03660

Not reached 15566 4.5981 2.47893 .01987

Levene's Test

for Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed 95.787 < 0.001

30.203 19325 < 0.001 1.33631 .04424 1.22234 1.45029

Equal

variances not

assumed

32.091 6173.842 < 0.001 1.33631 .04164 1.22902 1.44361

20

Table 21 - T-test results, Exposure - Discussion



Std.

Deviation

Std. Error

Mean

Average

discussion

frequency (0

to 10)

Regularly

reached 3772 5.6482 2.56913 .04183

Not reached 15783 4.4075 2.81353 .02240

Levene's Test

for Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed 56.431 < 0.001

24.731 19553 < 0.001 1.24071 .05017 1.11148 1.36995

Equal

variances not

assumed

26.148 6122.352 < 0.001 1.24071 .04745 1.11845 1.36297

Table 22 - T-test results, Exposure - Efficacy



Std.

Deviation

Std. Error

Mean

Efficacy (0 to

10)

Regularly

reached 3772 5.4748 1.78621 .02908

Not reached 15619 5.4201 1.92668 .01542

Levene's Test

for Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed 25.160 < 0.001

1.586 19389 .113 .05468 .03447 -.03413 0.14348

Equal

variances

not assumed

1.661 6072.102 .097 .05468 .03292 -.03014 0.13949

3.2 Outcome variables’ correlation

We tested the associations among the outcome variables, computing Pearson’s correlation

coefficients and testing for their significance. Significance tests were 1-tailed with α = 0.01.

All outcome variables are positively correlated each other. Pearson’s correlation are in all cases

significantly greater than 0 at 0.001 level. Correlations are moderate (> 0.3) in the cases of

Participation and Discussion, and of Discussion and Knowledge, while they are weak (> 0.1) for

21

Participation and Knowledge, Participation and Efficacy, and Knowledge and Efficacy. The correlation

between Discussion and Efficacy is very weak (< 0.1).

Table 23 reports coefficients and their significance.

Table 23 - Outcomes' correlation matrix

Average political

participation (0

to 10)

Average

discussion

frequency (0 to

10)

Average Self-

reported

knowledge (0 to

10)

Efficacy (0 to 10)

Average political

participation (0 to

10)

Pearson

Correlation 1 0.361 0.284 0.148

Sig. (1-tailed) < 0.001 < 0.001 < 0.001

N 23590 23388 23018 23121

Average discussion

frequency (0 to 10)

Pearson

Correlation 1 0.349 0.037

Sig. (1-tailed) < 0.001 < 0.001

N 23398 22918 22976

Average Self-

reported knowledge

(0 to 10)

Pearson

Correlation 1 0.112

Sig. (1-tailed) < 0.001

N 23030 22657

Efficacy (0 to 10)

Pearson

Correlation 1

Sig. (1-tailed)

N 23126

3.3 Exposure – confounders

We included several socio-demographic characteristics in the analysis. These have been selected as

potentially influencing factors, related to the outcome variables and/or to Exposure, which is the

hypothesised explanatory variable. Therefore, before including them in the multivariate regression

models, we tested their association with Exposure and with the outcome variables (see Par. 3.4).

3.3.1 Description of confounders

3.3.1.1 Gender

Table 24 - Distribution of frequencies, Gender


Valid

Male 11904 50.4 50.4 50.4

Female 11716 49.6 49.6 100.0

Total 23620 100.0 100.0

Missing System 1 .0

Total 23621 100.0

22

3.3.1.2 Age

We grouped the original Age (numeric) variable into a 6-category banded ordinal variable.

Table 25 - Distribution of frequencies, Age


Valid

15-24 7031 29.8 29.8 29.8

24-34 6869 29.1 29.1 58.9

35-44 4198 17.8 17.8 76.7

45-54 2720 11.5 11.5 88.2

55-64 1633 6.9 6.9 95.2

65+ 1140 4.8 4.8 100.0

Total 23591 99.9 100.0

Missing System 30 .1

Total 23621 100.0

3.3.1.3 Location

Table 26 - Distribution of frequencies, Location


Valid

Rural 15503 65.6 65.6 65.6

Urban 8118 34.4 34.4 100.0

Total 23621 100.0 100.0

3.3.1.4 Education level

Education is an ordinal variable derived from questions concerning both literacy and ‘formal’

education, in terms of completed levels of education. We classified everyone who stated that they

have major difficulties in reading a written text in their main language as ‘Non-literate’, regardless the

level of formal education declared.

Table 27 - Distribution of frequencies, Education


Valid

Non-literate 3836 16.2 16.6 16.6

Literate but not schooling 2937 12.4 12.7 29.3

Completed primary 5056 21.4 21.9 51.2

Completed secondary 7684 32.5 33.3 84.5

Completed higher education 3576 15.1 15.5 100.0

Total 23089 97.7 100.0

Missing Unknown 532 2.3

Total 23621 100.0

3.3.1.5 Income

Income is an ordinal variable that derives from a single question on the self-reported purchasing

power, for which the possible answers were:

We don’t have enough money, even for food;

We can afford food but purchasing of clothes is a serious problem;

23

We can afford food and clothes, but purchasing of durables such as a TV set or a

refrigerator is difficult for us;

We can afford main household appliances, but purchasing a car is beyond our means;

What we earn is sufficient to buy anything except such expensive purchases as an apartment

or house;

We do not face financial problems. If necessary we can buy an apartment or a house.

We considered the first two categories as ‘low’ income level, the third and the fourth as ‘medium’,

and the last two categories as ‘high’.

Table 28 - Distribution of frequencies, Income


Valid

Low 5652 23.9 24.9 24.9

Medium 15041 63.7 66.1 91.0

High 2047 8.7 9.0 100.0

Total 22740 96.3 100.0

Missing

DK 676 2.9 REF 205 .9 Total 881 3.7

Total 23621 100.0

3.3.1.6 Marital status

Table 29 - Distribution of frequencies, Marital status


Valid

Single 7304 30.9 31.3 31.3

Married, living with spouse 13132 55.6 56.3 87.7

Married, not living with spouse 1090 4.6 4.7 92.4

Divorced/separated 430 1.8 1.8 94.2

Widowed 953 4.0 4.1 98.3

In a marriage where the husband

has more than one wife 226 1.0 1.0 99.3

Living with partner 173 .7 .7 100.0

Total 23308 98.7 100.0

Missing System 313 1.3

Total 23621 100.0

3.3.1.7 Interest in politics

Interest is an ordinal variable specifying the self-reported measure of general interest in politics.

24

Table 30 - Distribution of frequencies, Interest


Valid

Not at all interested 3266 13.8 14.1 14.1

Not very interested 5525 23.4 23.8 37.9

Somewhat interested 7967 33.7 34.4 72.3

Very interested 6434 27.2 27.7 100.0

Total 23192 98.2 100.0

Missing

DK 216 .9 REF 22 .1 999 191 .8 Total 429 1.8

Total 23621 100.0

3.3.1.8 Group activity

This binary variable derives from questions about being an active member of any type of voluntary

groups (political, religious, civic associations, …). People who reported to be active members in at

least one group have been coded as active members.

Table 31 - Distribution of frequencies, Group activity


Valid

Not an active member 10883 46.1 46.1 46.1

Active member 12706 53.8 53.9 100.0

Total 23589 99.9 100.0

Missing System 32 .1

Total 23621 100.0

3.3.2 Exposure and categorical variables

Tables 32-36 show the results of Pearson’s Chi-square tests for cross-tabulation of Exposure by

categorical variables such as Gender, Location, Group activity, Country, and Marital status.

Table 32 - Cross-tabulation and Chi-Square test, Exposure by Gender

Sex of the respondent

Total Male Female

Exposure to at least

one governance

programme

Not

reached

Count 7735 8140 15875

Expected Count 8151.6 7723.4 15875

% within Exposure to at least one

governance programme 48.7% 51.3% 100.0%

Regularly

reached

Count 2356 1421 3777

Expected Count 1939.4 1837.6 3777



Total

Count 10091 9561 19652

Expected Count 10091 9561 19652



Chi-Square Tests

Value df Asymp. Sig.

(2-sided)

Pearson Chi-Square 227.664a 1 < 0.001

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is

1837.57.

25

Table 33 - Cross-tabulation and Chi-Square test, Exposure by Location

Location Total

Rural Urban


one governance

programme

Not

reached

Count 10025 5850 15875

Expected Count 10024.4 5850.6 15875



Regularly

reached

Count 2385 1393 3778

Expected Count 2385.6 1392.4 3778



Total

Count 12410 7243 19653




Chi-Square Tests


(2-sided)

Pearson Chi-Square 0.001 1 0.98

0 cells (0.0%) have expected count less than 5. The minimum expected count is

1392.36.

Table 34 - Cross-tabulation and Chi-Square test, Exposure by Group activity

Group activity (binary) Total

Not an active

member

Active

member


one governance

programme

Not

reached

Count 7639 8214 15853

Expected Count 7141.4 8711.6 15853



Regularly

reached

Count 1203 2572 3775

Expected Count 1700.6 2074.4 3775



Total

Count 8842 10786 19628




Chi-Square Tests


(2-sided)

Pearson Chi-Square 328.002 1 < 0.001

0 cells (0.0%) have expected count less than 5. The minimum expected count is 1700.56.

26

Table 35 - Cross-tabulation and Chi-Square test, Exposure by Country

Country Total

Bangladesh Nepal Kenya Nigeria Tanzania Sierra

Leone Myanmar

Exposure

to at least

one

governance

programme

Not

reached

Count 1869 2307 2094 2630 3425 2559 991 15875

Expected Count 1691.5 2615.5 1881.3 3065.5 3069.5 2698.7 853.0 15875

% within Exposure to at

least one governance

programme

89.3% 71.2% 89.9% 69.3% 90.1% 76.6% 93.8% 80.8%

Regularly

reached

Count 225 931 235 1165 375 782 65 3778

Expected Count 402.5 622.5 447.7 729.5 730.5 642.3 203.0 3778



programme

10.7% 28.8% 10.1% 30.7% 9.9% 23.4% 6.2% 19.2%

Total

Count 2094 3238 2329 3795 3800 3341 1056 19653

Expected Count 2094 3238 2329 3795 3800 3341 1056 19653



programme

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-

Square 1101.141 6 < 0.001

0 cells (0.0%) have expected count less than 5. The

minimum expected count is 203.00.

Table 36 - Cross-tabulation and Chi-Square test, Exposure by Marital status

Marital status Total

Single

Married,

living with

spouse

Married,

not living

with spouse

Divorced

/separated Widowed

In a

marriage

where the

husband has

more than

one wife

Living

with

partner

Exposure

to at least

one

governance

programme

Not

reached

Count 5179 8670 692 318 611 100 106 15676

Expected Count 5088.9 8755.7 713.5 291.4 558.5 157.4 110.6 15676

% within Exposure to

at least one

governance

programme

82.1% 79.9% 78.3% 88.1% 88.3% 51.3% 77.4% 80.7%

Regularly

reached

Count 1126 2178 192 43 81 95 31 3746

Expected Count 1216.1 2092.3 170.5 69.6 133.5 37.6 26.4 3746


at least one

governance

programme

17.9% 20.1% 21.7% 11.9% 11.7% 48.7% 22.6% 19.3%

Total

Count 6305 10848 884 361 692 195 137 19422

Expected Count 6305 10848 884 361 692 195 137 19422


at least one

governance

programme

100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson

Chi-Square 163.624 6 < 0.001

0 cells (0.0%) have expected count less than 5. The

minimum expected count is 26.42.

27

3.3.3 Exposure and ordinal variables

Table 37 shows the result of Matt-Whitney’s U-test for the association between Exposure and

ordinal variables such as Interest in politics, Age, Education, and Income.

Table 37 - Significance testing for Exposure and ordinal variables

Interest in politics Age in categories Education level Income

Not

reached Reached

Not

reached Reached

Not

reached Reached

Not

reached Reached

N 15687 3765 15860 3769 15543 3692 15291 3667

Mean rank 9198.6 11926 9751.78 10081.04 9213 11323 9391.88 9.844.85

Mann-Whitney U 37811888.5 30890889.5 34987282.5 29375788.5

Standard error 296593.407 303052.9 293538.319 242794.172

Standardised test

statistic 27.921 3.309 21.445 5.518

Asymptotic sig. (2-

sided test) < 0.001 0.001 < 0.001 < 0.001

3.4 Outcome variables – confounders

3.4.1 Participation

As described in the main report, Participation is significantly and positively associated to gender, age,

education, income, marital status, interest in politics and membership in groups.

3.4.1.1 Participation and categorical (binary) variables

Tables 38-40 report the results of t-tests where the difference in Participation means is analysed for

groups defined by binary variables such as gender, location, and membership in groups.

Table 38 - T-test results, Gender - Participation

Sex of the respondent N Mean Std.

Deviation

Std. Error

Mean

Average

political

participation

(0 to 10)

Male 11891 4.1550 2.19198 .02010

Female 11698 3.2692 1.87525 .01734

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

496.947 < 0.001

33.326 23587 < 0.001 .88579 .02658 .81732 0.95426

Equal

variances

not

assumed

33.368 23142.228 < 0.001 .88579 .02655 .81741 0.95417

28

Table 39 - T-test results, Location - Participation

Location N Mean Std.

Deviation

Std. Error

Mean

Average

political

participation

(0 to 10)

Rural 15488 3.7882 2.06601 .01660

Urban 8102 3.5772 2.12402 .02360

Levene's Test

for Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

1.415 .234

7.377 23588 < 0.001 .21099 .02860 .13731 0.28467

Equal

variances

not

assumed

7.313 16047.995 < 0.001 .21099 .02885 .13666 0.28531

Table 40 - T-test results, Group activity - Participation

Group activity N Mean Std.

Deviation

Std. Error

Mean

Average

political

participation

(0 to 10)

Not an

active

member

10854 3.0585 1.72183 .01653

Active

member 12705 4.2778 2.20516 .01956

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

1218.71 < 0.001

-46.712 23557 < 0.001 -1.21932 .02610 -1.287 -1.152

Equal

variances

not

assumed

-47.611 23372.713 < 0.001 -1.21932 .02561 -1.285 -1.153

3.4.1.2 Participation and categorical variables

Tables 41-42 report mean scores and ANOVA for Participation, based on groups defined by

categorical variables such as country and marital status.

29

Table 41 - ANOVA for Participation, by Country

Average political

participation (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Bangladesh 2650 3.2388 1.50744 .02928 3.1814 3.2963

Nepal 4000 3.3314 1.93867 .03065 3.2713 3.3914

Kenya 3002 4.6001 2.15373 .03931 4.5231 4.6772

Nigeria 4239 3.3922 2.26551 .03480 3.3240 3.4604

Tanzania 4111 3.3752 1.84620 .02879 3.3188 3.4317

Sierra Leone 4367 4.4461 2.23546 .03383 4.3798 4.5125

Myanmar 1221 3.4929 1.69080 .04839 3.3980 3.5879

Total 23590 3.7157 2.08847 .01360 3.6891 3.7424

Model

Fixed

Effects 2.01798 .01314 3.6900 3.7415

Random

Effects .23270 3.1463 4.2851

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 6852.578 6 1142.096

280.458 < 0.001 Within

Groups 96036.102 23583 4.072

Total 102888.680 23589

Table 42 - ANOVA for Participation, by Marital Status

Average political

participation (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Single 7298 3.2307 1.99696 .02338 3.1849 3.2765

Married, living with

spouse 13129 3.9099 2.06596 .01803 3.8746 3.9453

Married, not living with

spouse 1089 4.2354 2.19225 .06643 4.1050 4.3657

Divorced/separated 430 3.8234 2.11390 .10194 3.6230 4.0237

Widowed 951 3.6981 2.00756 .06510 3.5703 3.8258

In a marriage where the

husband has more than

one wife

226 5.3215 2.24953 .14964 5.0267 5.6164

Living with partner 173 3.8730 2.54996 .19387 3.4904 4.2557

Total 23296 3.7155 2.08699 .01367 3.6887 3.7423

Model

Fixed

Effects 2.05514 .01346 3.6891 3.7419

Random

Effects .30942 2.9584 4.4726

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 3098.332 6 516.389

122.262 < 0.001 Within

Groups 98363.601 23289 4.224

Total 101461.933 23295

30

3.4.1.3 Participation and ordinal variables

Table 43 reports Spearman’s ρ correlation coefficients and their significance in a two-tailed

significance test. Participation is significantly associated with all of the four ordinal variables. The

association is positive in all cases except income.

Table 43 - Correlation coefficients for Participation and ordinal variables

Interest in

politics Age in categories Education level Income

Average political

participation (0 to

10)

Spearman's ρ 0.286 0.208 0.073 -0.075

Sig. (2-tailed) < 0.001 < 0.001 < 0.001 < 0.001

N 23186 23562 23074 22729

3.4.2 Knowledge

As described in the main report, bivariate analysis showed that Knowledge is associated with gender,

location, age, education, income, marital status, interest in politics and membership in groups.

3.4.2.1 Knowledge and categorical (binary) variables

Tables 44-46 report the results of t-tests where the difference in Knowledge average scores is

analysed for groups defined by binary variables such as gender, location, and membership in groups.

Table 44 - T-test results, Gender - Knowledge



Std.

Deviation

Std. Error

Mean

Average Self-

reported

knowledge (0

to 10)

Male 11724 5.0661 2.47966 .02290

Female 11305 4.4737 2.53391 .02383

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

13.537 < 0.001

17.933 23027 < 0.001 .59247 .03304 .50736 0.67757

Equal

variances

not

assumed

17.926 22949.736 < 0.001 .59247 .03305 .50732 0.67761

31

Table 45 - T-test results, Location - Knowledge


Deviation

Std. Error

Mean

Average Self-

reported

knowledge (0

to 10)

Rural 15035 4.6306 2.48644 .02028

Urban 7995 5.0472 2.57077 .02875

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

8.755 .003

-11.962 23028 < 0.001 -.41660 .03483 -.506 -0.327

Equal

variances

not

assumed

-11.841 15840.978 < 0.001 -.41660 .03518 -.507 -0.326

Table 46 - T-test results, Group activity - Knowledge


Deviation

Std. Error

Mean

Average Self-

reported

knowledge (0

to 10)

Not an

active

member

10439 4.3486 2.51740 .02464

Active

member 12565 5.1304 2.47277 .02206

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

15.958 < 0.001

-23.678 23002 < 0.001 -.78178 .03302 -.867 -0.697

Equal

variances

not

assumed

-23.639 22088.002 < 0.001 -.78178 .03307 -.867 -0.697

3.4.2.2 Knowledge and categorical variables

Tables 47-48 report mean scores and ANOVA for Knowledge, based on groups defined by


32

Table 47 - ANOVA for Knowledge, by Country

Average Self-reported

knowledge (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Bangladesh 2507 4.8710 2.67833 .05349 4.7661 4.9759

Nepal 3850 4.9613 1.91733 .03090 4.9007 5.0219

Kenya 2984 5.2149 2.44447 .04475 5.1272 5.3027

Nigeria 4193 5.1149 2.78798 .04306 5.0305 5.1993

Tanzania 4097 4.5550 2.45998 .03843 4.4796 4.6303

Sierra Leone 4186 4.6125 2.64102 .04082 4.5324 4.6925

Myanmar 1213 3.0363 2.02621 .05818 2.9221 3.1504

Total 23030 4.7752 2.52378 .01663 4.7426 4.8078

Model

Fixed

Effects 2.47901 .01634 4.7432 4.8072

Random

Effects .20504 4.2735 5.2769

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 5194.840 6 865.807

140.885 < 0.001 Within

Groups 141487.895 23023 6.146

Total 146682.735 23029

Table 48 - ANOVA for Knowledge, by Marital Status

Average Self-reported

knowledge (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Single 7179 4.7504 2.64019 .03116 4.6893 4.8115


spouse 12760 4.8233 2.44178 .02162 4.7810 4.8657


spouse 1070 4.9924 2.51128 .07677 4.8417 5.1430


Widowed 924 4.0405 2.51010 .08258 3.8784 4.2025



one wife

223 5.4931 2.77941 .18612 5.1263 5.8599


Total 22744 4.7775 2.52458 .01674 4.7447 4.8103

Model

Fixed

Effects 2.51827 .01670 4.7448 4.8102

Random

Effects .15230 4.4048 5.1501

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 761.503 6 126.917

20.013 < 0.001 Within

Groups 144190.704 22737 6.342

Total 144952.207 22743

33

3.4.2.3 Knowledge and ordinal variables


significance test. Knowledge is significantly associated with all of the four variables, although the

correlation is very weak with Age. Interest is moderately correlated with Knowledge, while the

correlation is weak for Education and even weaker for Income. All of the correlations are positive.

Table 49 - Correlation coefficients for Knowledge and ordinal variables

Interest in


Average Self-

reported knowledge

(0 to 10)

Spearman's ρ 0.334 0.024 0.267 0.122

Sig. (2-tailed) < 0.001 < 0.001 < 0.001 < 0.001

N 22713 23002 22519 22180

3.4.3 Discussion

As described in the main report, bivariate analysis showed that Discussion is associated with gender,

location, education, income, marital status, interest in politics and membership in groups.

3.4.3.1 Discussion and categorical (binary) variables

Tables 50-52 report the results of t-tests where the difference in Discussion average scores is

analysed for groups defined by binary variables such as gender, location, and membership in groups.

Table 50 - T-test results, Gender - Discussion



Std.

Deviation

Std. Error

Mean

Average

discussion

frequency (0

to 10)

Male 11816 4.9674 2.76922 .02548

Female 11581 4.1046 2.80766 .02609

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

69.798 < 0.001

23.664 23395 < 0.001 .86278 .03646 .76886 0.95670

Equal

variances

not

assumed

23.661 23368.188 < 0.001 .86278 .03646 .76884 0.95671

34

Table 51 - T-test results, Location - Discussion


Deviation

Std. Error

Mean

Average

discussion

frequency (0

to 10)

Rural 15332 4.4033 2.84177 .02295

Urban 8066 4.8010 2.76365 .03077

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

50.443 < 0.001

-10.272 23396 < 0.001 -.39775 .03872 -.498 -0.298

Equal

variances

not

assumed

-10.361 16798.447 < 0.001 -.39775 .03839 -.497 -0.299

Table 52 - T-test results, Group activity - Discussion


Deviation

Std. Error

Mean

Average

discussion

frequency (0

to 10)

Not an

active

member

10712 3.6561 2.72636 .02634

Active

member 12657 5.2920 2.67855 .02381

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

38.916 < 0.001

-46.140 23367 < 0.001 -1.63590 .03545 -1.727 -1.545

Equal

variances

not

assumed

-46.072 22596.560 < 0.001 -1.63590 .03551 -1.727 -1.544

3.4.3.2 Discussion and categorical variables

Tables 53-54 report mean scores and ANOVA for Discussion, based on groups defined by


35

Table 53 - ANOVA for Discussion, by Country

Average discussion

frequency (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Bangladesh 2635 2.9972 2.27356 .04429 2.9103 3.0840

Nepal 3967 4.1202 2.60827 .04141 4.0391 4.2014

Kenya 3000 5.1956 2.58111 .04712 5.1032 5.2880

Nigeria 4226 5.0487 2.70572 .04162 4.9671 5.1303

Tanzania 4106 4.7954 3.07903 .04805 4.7012 4.8896

Sierra Leone 4265 5.4177 2.60040 .03982 5.3397 5.4958

Myanmar 1199 1.8967 2.18122 .06299 1.7731 2.0203

Total 23398 4.5404 2.82137 .01844 4.5042 4.5765

Model

Fixed

Effects 2.65559 .01736 4.5064 4.5744

Random

Effects .41178 3.5328 5.5480

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 21285.220 6 3547.537

503.042 < 0.001 Within

Groups 164957.377 23391 7.052

Total 186242.597 23397

Table 54 - ANOVA for Discussion, by Marital Status

Average discussion

frequency (0 to 10) N Mean

Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Single 7265 4.6536 2.73961 .03214 4.5906 4.7166


spouse 13009 4.4667 2.81428 .02467 4.4183 4.5150


spouse 1077 5.0433 2.85043 .08686 4.8729 5.2138


Widowed 944 3.5231 2.85366 .09288 3.3409 3.7054



one wife

224 6.7857 2.92928 .19572 6.4000 7.1714


Total 23109 4.5408 2.82043 .01855 4.5044 4.5772

Model

Fixed

Effects 2.80113 .01843 4.5047 4.5769

Random

Effects .28094 3.8534 5.2282

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 2554.316 6 425.719

54.257 < 0.001 Within

Groups 181265.856 23102 7.846

Total 183820.172 23108

36

3.4.3.3 Discussion and ordinal variables


significance test. Discussion is significantly associated with Interest, Education, and Income, although

its correlation with the latter is very weak. The association is positive in all cases. Discussion is not

correlated with age.

Table 55 - Correlation coefficients for Discussion and ordinal variables

Interest in


Average discussion

frequency (0 to 10)

Spearman's ρ 0.287 -0.004 0.211 0.048

Sig. (2-tailed) < 0.001 0.269 < 0.001 < 0.001

N 23043 23370 22887 22547

3.4.4 Efficacy

As described in the main report, bivariate analysis showed that Efficacy is associated with gender,

location, age, education, income, marital status, interest in politics and membership in groups.

3.4.4.1 Efficacy and categorical (binary) variables

Tables 56-57 report the results of t-tests where the difference in Efficacy average scores is analysed

for groups defined by binary variables such as gender, location, and membership in groups.

Table 56 - T-test results, Gender - Efficacy



Std.

Deviation

Std. Error

Mean

Efficacy (0 to

10)

Male 11744 5.4965 1.88177 .01736

Female 11381 5.3683 1.92414 .01804

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

5.209 .022

5.122 23123 < 0.001 .12819 .02503 .06372 0.19266

Equal

variances

not

assumed

5.120 23056.638 < 0.001 .12819 .02504 .06370 0.19269

37

Table 57 - T-test results, Location - Efficacy


Deviation

Std. Error

Mean

Efficacy (0 to

10)

Rural 8034 5.1995 1.94903 .02174

Urban 15092 5.5578 1.86738 .01520

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

26.047 < 0.001

-13.680 23124 < 0.001 -.35823 .02619 -.426 -0.291

Equal

variances

not

assumed

-13.503 15794.561 < 0.001 -.35823 .02653 -.427 -0.290

Table 58 - T-test results, Group activity - Efficacy


Deviation

Std. Error

Mean

Efficacy (0 to

10)

Not an

active

member

10477 5.4857 1.95323 .01908

Active

member 12626 5.3900 1.86089 .01656

Levene's Test for

Equality of

Variances



tailed)

Mean

Difference

Std. Error

Difference

99% Confidence

Interval of the

Difference

Lower Upper

Equal

variances

assumed

24.426 < 0.001

3.807 23101 < 0.001 .09576 .02515 .03097 0.16056

Equal

variances

not

assumed

3.790 21893.795 < 0.001 .09576 .02527 .03067 0.16085

3.4.4.2 Efficacy and categorical variables

Tables 59-60 report mean scores and ANOVA for Efficacy, based on groups defined by categorical

variables such as country and marital status.

38

Table 59 - ANOVA for Efficacy, by Country

Efficacy (0 to 10) N Mean Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Bangladesh 2591 6.2951 2.05842 .04044 6.2158 6.3744

Nepal 3897 5.4621 1.34724 .02158 5.4198 5.5044

Kenya 3003 5.6782 1.67673 .03060 5.6182 5.7382

Nigeria 4205 4.7405 1.99119 .03071 4.6803 4.8007

Tanzania 4100 5.4216 1.94450 .03037 5.3620 5.4811

Sierra Leone 4241 5.1140 1.95129 .02996 5.0553 5.1727

Myanmar 1089 6.5675 1.67598 .05079 6.4679 6.6672

Total 23126 5.4333 1.90376 .01252 5.4088 5.4578

Model

Fixed

Effects 1.83506 .01207 5.4097 5.4570

Random

Effects .21999 4.8950 5.9716

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 5959.882 6 993.314

294.975 < 0.001 Within

Groups 77852.174 23119 3.367

Total 83812.056 23125

Table 60 - ANOVA for Efficacy, by Marital Status

Efficacy (0 to 10) N Mean Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Lower

Bound

Upper

Bound

Single 7193 5.2688 1.91970 .02263 5.2244 4.8115


spouse 12867 5.5592 1.89128 .01667 5.5265 4.8657


spouse 1071 5.1664 1.84978 .05652 5.0554 5.1430


Widowed 897 5.4832 1.88203 .06284 5.3599 4.2025



one wife

226 5.2099 1.85296 .12326 4.9670 5.8599


Total 22844 5.4383 1.90243 .01259 5.4136 4.8103

Model

Fixed

Effects 1.89674 .01255 5.4137 4.8102

Random

Effects .12588 5.1303 5.1501

ANOVA

Sum of

Squares df

Mean

Square F Sig.

Between

Groups 515.229 6 85.872

23.869 < 0.001 Within

Groups 82159.295 22837 3.598

Total 82674.525 22843

39

3.4.4.3 Efficacy and ordinal variables


significance test. Efficacy is significantly associated with all of the four variables except Income. The

correlation is positive and weak with Interest, and positive and very weak with age. Efficacy is

negatively and very weakly associated with Education.

Table 61 - Correlation coefficients for Efficacy and ordinal variables

Interest in


Efficacy (0 to 10)

Spearman's ρ 0.155 0.069 -0.033 -0.007

Sig. (2-tailed) < 0.001 < 0.001 < 0.001 0.139

N 22824 23098 22627 22288

40

4 Multivariate regression analysis

This section details the process undertaken to build multivariate regression models to evaluate the

relationship between exposure to BBC Media Action programming and outcomes variables

(Participation, Discussion, Knowledge, and Efficacy). As described in the previous sections, we

defined the outcome variables (see Section 2), the hypothesised explanatory variable (Exposure, see

section 3.1.1), and confounders (see Section 3.3.1) and tested their mutual associations (see Section

3).

OLS regression models assessed the association between the predictors and the construct

outcomes. Categorical and ordinal confounders were introduced into the model as dummy variables,

with a single dummy for each ‘level’ or ‘category’ apart from the reference category.

For each categorical confounder, we set the reference category as that with the largest number of

cases. This is the case of Gender (Male is the reference category since it has 11904 cases, i.e. 50.4%

of total), Location (Rural = 15503, i.e. 65.6% of total), and Marital status (“Married, living with

spouse” = 13132, i.e. 55.6%). Also the Country variable’s reference category is the largest sized

(Sierra Leone = 4389 cases, i.e. 18.6% of total).

For ordinal confounders (Age, Education, and Interest in politics), the reference category is the

lowest one. For Income we set the “Medium” level as the reference category, since it is the largest

(15041, i.e. 63.7% of total) and also the most common from a conceptual point of view.

For Group activity, the reference category is “Not an active member”.

For each of the outcome variables, we developed four OLS models. The first includes Exposure as

the hypothesised explanatory variable and the full list of confounders (Gender, Age, Location,

Education, Income, Marital status, Interest in politics, and Group activity), together with the Country

variable. We introduced the predictors in three blocks in order to observe the change in R2 and F.

We introduced Exposure in the first block, socio-political confounders (Interest in politics and

Group activity) in the second one, and demographic confounders in the third one (Gender, Age,

Location, Education, Income, Marital status), together with the Country variable.

The second model includes the interaction between Exposure and Gender. We are particularly

interested in checking whether the association between Exposure and the outcomes is significantly

different for men and women, so we built specific models to test this. For these models, we included

the Gender variable together with the interaction term (Exposure for Women) as a second block,

after Exposure. Socio-political confounders were included as a third block and demographic

confounders (included Country) as a fourth one.

The third model includes all of the interaction terms that proved to be significant. At this stage, we

tested for significance of interactions between the Exposure variable and all of the confounders

(both socio-political and demographic). We included all the interactions that remained significant in a

single model, where we included Exposure as a first block, each interaction term with the

corresponding confounders as a single block, and the all the confounders that do not interact

significantly with Exposure as a last block.

The fourth model includes only interactions with the Country variable. This is specifically aimed at

checking whether the main results are consistent across countries. In this case we included

41

Exposure as the first block, the interaction terms and the country dummies as the second one, the

socio-political confounders as the third one, and the demographic confounders as the fourth one.

For each of the above described model we report in this appendix:

a model summary, including:

- the R, the R2, and the adjusted R2 of the model,

- the standard error of the estimate,

- the R2 and the F changes, their degrees of freedom, and the significance of the F change.

ANOVA table, including:

- the total, model’s and residual Sum of Squares,

- the mean square,

- the F-value and its significance.

coefficients’ table, including:

- B coefficients and their standard errors,

- standardised Beta coefficients,

- t-statistics,

- significance values,

- 99% confidence intervals of the B coefficients,

- tolerance and Variance Inflation Factors (VIFs).

a diagnostics section, including:

- model’s number of cases, outliers (standardised residuals > |3|) and influential cases

(Cook’s distance > |1|);

- model’s Durbin-Watson statistic;

- a scatterplot of the model’s standardised residuals against their predicted values.

Table 62 - List of regression models

Outcome

variable

Model n. 1

(no interactions)

Model n. 2

(interaction with

Gender)

Model n. 3

(interaction with

other confounders)

Model n. 4

(interaction with

Country)

Participation ‎4.1.1 ‎4.1.2 ‎4.1.3 ‎4.1.4

Knowledge ‎4.2.1 ‎4.2.2 ‎4.2.3 ‎4.2.4

Discussion ‎4.3.1 ‎4.3.2 ‎4.3.3 ‎4.3.4

Efficacy ‎4.4.1 ‎4.4.2 ‎4.4.3 ‎4.4.4

42

4.1 Regression models – Participation

4.1.1 Model n. 1 – Exposure with all confounders

4.1.1.1 Model summary

The model includes 23621 observations. Missing data were handled using pair-wise deletion. 18320

cases have no missing data.

Table 63 - Model n. 1 summary - Participation

Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2

Change F Change df1 df2

Sig. F

Change

1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001

2 0.398 0.158 0.158 1.917 0.123 690.582 4 18952 < 0.001

3 0.538 0.289 0.288 1.762 0.131 139.471 25 18927 < 0.001

4.1.1.2 ANOVA

Table 64 – Model n. 1 ANOVA - Participation

Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 2922.807 1 2922.807 694.622 < 0.001

Residual 79762.372 18956 4.208

Total 82685.180 18957

2

Regression 13069.555 5 2613.911 711.605 < 0.001

Residual 69615.625 18952 3.673

Total 82685.180 18957

3

Regression 23899.267 30 796.642 256.491 < 0.001

Residual 58785.912 18927 3.106

Total 82685.180 18957

4.1.1.3 Coefficients

Significance testing was conducted using the parameters test and an examination of the t-statistic in

the parameter estimate tables.

Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic

well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.643.

43

Table 65 - Model n. 1 regression coefficients - Participation

Coefficients

t Sig.

99% Confidence

Interval for B Collinearity Statistics

B Std. Error Beta Lower

Bound

Upper

Bound Tolerance VIF

(Constant) 2.828 .071 39.726 < 0.001 2.645 3.012

Exposure to at least one governance

programme .530 .035 .100 15.175 < 0.001 .440 .620 .865 1.156

Sex of the respondent – Female -.550 .027 -.132 -20.303 < 0.001 -.620 -.481 .892 1.121

Group activity (binary) – Active members .804 .031 .192 26.169 < 0.001 .725 .883 .699 1.430

Interest in politics - Not very interested .264 .043 .054 6.074 < 0.001 .152 .376 .478 2.094

Interest in politics - Somewhat interested .687 .042 .156 16.406 < 0.001 .579 .795 .414 2.414

Interest in politics - Very interested 1.267 .045 .272 28.191 < 0.001 1.151 1.383 .405 2.471

Country - Bangladesh -.567 .056 -.086 -10.210 < 0.001 -.710 -.424 .534 1.874

Country - Nepal -1.204 .049 -.216 -24.779 < 0.001 -1.330 -1.079 .493 2.029

Country - Kenya .043 .049 .007 .866 .386 -.084 .170 .605 1.653

Country - Nigeria -.981 .046 -.180 -21.133 < 0.001 -1.100 -.861 .516 1.936

Country - Tanzania -1.033 .048 -.188 -21.484 < 0.001 -1.157 -.909 .492 2.031

Country - Myanmar -.532 .070 -.056 -7.647 < 0.001 -.711 -.353 .690 1.450

Location – Urban -.254 .030 -.058 -8.534 < 0.001 -.331 -.177 .819 1.221

Age groups - 25-34 .400 .037 .087 10.744 < 0.001 .304 .496 .573 1.744

Age groups - 35-44 .577 .045 .106 12.913 < 0.001 .462 .692 .561 1.783

Age groups - 45-54 .821 .051 .126 16.061 < 0.001 .690 .953 .614 1.628

Age groups - 55-64 .938 .061 .114 15.365 < 0.001 .780 1.095 .683 1.465

Age groups - 65+ 1.026 .071 .105 14.496 < 0.001 .844 1.208 .711 1.406

Education - Literate .217 .049 .035 4.382 < 0.001 .089 .344 .604 1.655

Education - Completed primary .411 .046 .081 8.848 < 0.001 .291 .531 .443 2.255

Education - Completed secondary .440 .045 .099 9.886 < 0.001 .326 .555 .372 2.687

Education - Completed college or university .792 .053 .137 14.896 < 0.001 .655 .929 .443 2.259

Income - Low (can afford food at most) .195 .034 .040 5.815 < 0.001 .109 .282 .777 1.287

Income - High (can afford almost

everything) -.011 .048 -.002 -0.239 .811 -.135 .112 .869 1.151

Marital Status - Single -.482 .037 -.107 -13.137 < 0.001 -.576 -.387 .566 1.767

Marital Status - Married, not living with

spouse -.073 .063 -.007 -1.163 .245 -.234 .088 .939 1.065

Marital Status - Divorced/Separated -.182 .097 -.012 -1.878 .060 -.432 .068 .961 1.040

Marital Status - Widowed -.097 .069 -.009 -1.409 .159 -.275 .081 .877 1.140

Marital Status - In a marriage where the

husband has more than on wife .735 .134 .034 5.491 < 0.001 .390 1.079 .953 1.049

Marital Status - Living with partner .035 .151 .001 .228 .820 -.355 .425 .970 1.031

4.1.1.4 Diagnostics

Table 66 - Model n. 1 diagnostics - Participation

N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.26% 1.35% 5.45% 0.00% 1.643

44

Figure 9 - Residuals and predicted values - Model n. 1 - Participation

4.1.2 Model n. 2 – Exposure & Gender interaction



Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001

2 0.271 0.073 0.073 2.011 0.038 387.690 2 18954 < 0.001

3 0.429 0.184 0.184 1.887 0.111 643.902 4 18950 < 0.001

4 0.538 0.289 0.288 1.762 0.105 116.890 24 18926 < 0.001

45

4.1.2.2 ANOVA

Table 68 - Model n. 2 ANOVA - Participation

Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 2922.807 1 2922.807 694.622 < 0.001

Residual 79762.372 18956 4.208

Total 82685.180 18957

2

Regression 6057.533 3 2019.178 499.448 < 0.001

Residual 76627.647 18954 4.043

Total 82685.180 18957

3

Regression 15226.282 7 2175.183 611.035 < 0.001

Residual 67458.898 18950 3.560

Total 82685.180 18957

4

Regression 23934.711 31 772.087 248.722 < 0.001

Residual 58750.469 18926 3.104

Total 82685.180 18957






46


Coefficients

t Sig.

99% Confidence

Interval for B Collinearity Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.809 .071 39.338 < 0.001 2.625 2.993


programme .621 .044 .117 14.067 < 0.001 .507 .735 .541 1.850


Exposure for women -.237 .070 -.028 -3.379 .001 -.418 -.056 .545 1.836

Group activity – Active members .803 .031 .192 26.143 < 0.001 .724 .882 .699 1.431





Country - Nepal -1.213 .049 -.218 -24.929 < 0.001 -1.338 -1.088 .492 2.034

Country - Kenya .042 .049 .007 .841 .400 -.086 .169 .605 1.653

Country - Nigeria -.978 .046 -.180 -21.085 < 0.001 -1.098 -.859 .516 1.937


Country - Myanmar -.531 .070 -.056 -7.632 < 0.001 -.710 -.351 .690 1.450

Location – Urban -.255 .030 -.058 -8.560 < 0.001 -.332 -.178 .819 1.221

Age groups - 25-34 .398 .037 .087 10.697 < 0.001 .302 .494 .573 1.744

Age groups - 35-44 .573 .045 .105 12.826 < 0.001 .458 .688 .560 1.784

Age groups - 45-54 .816 .051 .125 15.966 < 0.001 .685 .948 .614 1.629

Age groups - 55-64 .935 .061 .114 15.322 < 0.001 .778 1.092 .683 1.465

Age groups - 65+ 1.027 .071 .105 14.515 < 0.001 .845 1.209 .711 1.406






Income - High (can afford almost

everything) -.011 .048 -.002 -0.237 .813 -.135 .112 .869 1.151


Marital Status - Married, not living with

spouse -.071 .063 -.007 -1.129 .259 -.232 .091 .939 1.065



Marital Status - In a marriage where the

husband has more than on wife .728 .134 .034 5.440 < 0.001 .383 1.072 .953 1.049


4.1.2.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.26% 1.36% 5.53% 0.00% 1.642

47


4.1.3 Model n. 3 – Exposure & significant interactions



Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 .188a 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001

2 .271b 0.073 0.073 2.011 0.038 387.690 2 18954 < 0.001

3 .333c 0.111 0.111 1.970 0.038 80.752 10 18944 < 0.001

4 .360d 0.129 0.128 1.950 0.018 49.237 8 18936 < 0.001

5 .434e 0.188 0.187 1.883 0.059 690.689 2 18934 < 0.001

6 .476f 0.227 0.226 1.838 0.038 157.076 6 18928 < 0.001

7 .542g 0.294 0.292 1.757 0.067 119.178 15 18913 < 0.001

48

4.1.3.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 2922.807 1 2922.807 694.622 < 0.001

Residual 79762.372 18956 4.208

Total 82685.180 18957

2

Regression 6057.533 3 2019.178 499.448 < 0.001

Residual 76627.647 18954 4.043

Total 82685.180 18957

3

Regression 9190.377 13 706.952 182.224 < 0.001

Residual 73494.803 18944 3.880

Total 82685.180 18957

4

Regression 10688.010 21 508.953 133.860 < 0.001

Residual 71997.170 18936 3.802

Total 82685.180 18957

5

Regression 15583.575 23 677.547 191.183 < 0.001

Residual 67101.605 18934 3.544

Total 82685.180 18957

6

Regression 18766.209 29 647.111 191.626 < 0.001

Residual 63918.971 18928 3.377

Total 82685.180 18957

7

Regression 24286.123 44 551.957 178.756 < 0.001

Residual 58399.057 18913 3.088

Total 82685.180 18957




Multicollinearity testing revealed that, apart from Exposure and its interactions, all variables were

acceptable, with a tolerance statistic well above 0.2 for all variables. The average Variance Inflation

Factor (VIF) is 3.289.

49


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.558 .078 32.826 < 0.001 2.357 2.758


programme 1.985 .175 .375 11.359 < 0.001 1.535 2.435 .034 29.119

Sex of the respondent – Women -.492 .030 -.118 -16.485 < 0.001 -.569 -.415 .732 1.365

Exposure for women -.309 .072 -.037 -4.288 < 0.001 -.494 -.123 .513 1.948

Age groups - 25-34 .450 .042 .098 10.698 < 0.001 .342 .558 .446 2.242

Exposure for 25-34 -.228 .094 -.024 -2.417 .016 -.472 .015 .368 2.716

Age groups - 35-44 .674 .050 .123 13.442 < 0.001 .544 .803 .444 2.255

Exposure for 35-44 -0.428 .109 -.036 -3.910 < 0.001 -0.710 -0.146 .448 2.231

Age groups - 45-54 .887 .058 .136 15.320 < 0.001 .738 1.036 .477 2.097

Exposure for 45-54 -0.289 .125 -.020 -2.300 .021 -0.612 0.035 .497 2.013

Age groups - 55-64 1.017 .068 .124 14.901 < 0.001 .841 1.192 .543 1.841

Exposure for 55-64 -.325 .159 -.016 -2.045 .041 -0.735 .085 .612 1.633

Age groups - 65+ 1.139 .077 .117 14.709 < 0.001 0.940 1.338 .591 1.693

Exposure for 65 or more -.526 .207 -.018 -2.542 .011 -1.059 .007 .709 1.410

Education - Literate .261 .056 .042 4.687 < 0.001 0.117 .404 .474 2.109

Exposure for Literate -.152 .166 -.009 -0.915 .360 -0.578 .275 .361 2.774

Education - Completed primary .507 .052 .100 9.766 < 0.001 0.374 .641 .353 2.835

Exposure for Primary -.447 .152 -.032 -2.938 .003 -0.839 -.055 .310 3.226

Education - Completed secondary .567 .051 .128 11.027 < 0.001 0.435 .699 .277 3.604

Exposure for Secondary -.560 .136 -.067 -4.108 < 0.001 -0.912 -.209 .142 7.041

Education - Completed college or university .886 .062 .154 14.261 < 0.001 0.726 1.046 .322 3.104

Exposure for High educated -.456 .148 -.044 -3.081 .002 -0.837 -.075 .182 5.491

Group activity – Active members .737 .034 .176 21.794 < 0.001 0.650 .824 .573 1.744

Exposure for Active members .296 .075 .046 3.972 < 0.001 0.104 .489 .280 3.572

Interest in politics - Not very interested .419 .048 .085 8.685 < 0.001 0.295 .543 .386 2.590

Exposure for Not very interested -1.231 .175 -.092 -7.050 < 0.001 -1.681 -.781 .218 4.596


Exposure for Somewhat interested -1.025 .164 -.117 -6.259 < 0.001 -1.447 -.603 .106 9.437


Exposure for Very interested -.967 .167 -.121 -5.800 < 0.001 -1.397 -.538 .085 11.732


Country - Nepal -1.209 .049 -.217 -24.843 < 0.001 -1.334 -1.083 .489 2.045

Country - Kenya .050 .049 .008 1.010 .313 -.077 0.177 .603 1.658

Country - Nigeria -.978 .046 -.180 -21.046 < 0.001 -1.098 -.858 .512 1.953


Country - Myanmar -.520 .070 -.055 -7.447 < 0.001 -.700 -.340 .679 1.472

Location – Urban -.242 .030 -.055 -8.149 < 0.001 -.319 -.166 .816 1.226


Income - High (can afford almost everything) -.006 .048 -.001 -0.131 .896 -.130 .117 .869 1.151


Marital Status - Married, not living with spouse -.069 .062 -.007 -1.103 .270 -.230 .092 .938 1.066



Marital Status - In a marriage where the husband

has more than on wife .629 .136 .030 4.626 < 0.001 .279 0.980 .916 1.091


50

4.1.3.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.28% 1.48% 5.73% 0.00% 1.642


4.1.4 Model n. 4 – Exposure & Country interactions



Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001

2 0.331 0.110 0.109 1.971 0.074 131.879 12 18944 < 0.001

3 0.465 0.216 0.216 1.850 0.107 643.499 4 18940 < 0.001

4 0.54 0.291 0.290 1.760 0.075 105.252 19 18921 < 0.001

51

4.1.4.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 2922.807 1 2922.807 694.622 < 0.001

Residual 79762.372 18956 4.208

Total 82685.180 18957

2

Regression 9072.281 13 697.868 179.594 < 0.001

Residual 73612.899 18944 3.886

Total 82685.180 18957

3

Regression 17879.544 17 1051.738 307.379 < 0.001

Residual 64805.636 18940 3.422

Total 82685.180 18957

4

Regression 24074.216 36 668.728 215.881 < 0.001

Residual 58610.963 18921 3.098

Total 82685.180 18957




Multicollinearity testing revealed that Exposure is the only variable with Tolerance level below 0.2,

which is due to its interactions with the country categories. The average Variance Inflation Factor

(VIF) is 1.934.

52


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.964 .074 39.916 < 0.001 2.773 3.155


programme .112 .077 .021 1.458 .145 -.086 .310 .178 5.625


Exposure for Bangladesh .318 .161 .015 1.977 .048 -.096 .733 .652 1.533

Country - Nepal -1.392 .058 -.250 -24.132 < 0.001 -1.541 -1.244 .349 2.866

Exposure for Nepal .693 .113 .066 6.133 < 0.001 .402 .984 .328 3.052

Country - Kenya -.053 .055 -.008 -0.965 .335 -.194 .088 .489 2.043

Exposure for Kenya .241 .157 .012 1.529 .126 -.165 .646 .651 1.536

Country - Nigeria -1.174 .056 -.216 -21.088 < 0.001 -1.317 -1.030 .358 2.792

Exposure for Nigeria .701 .108 .073 6.470 < 0.001 .422 .979 .292 3.425

Country - Tanzania -1.151 .054 -.209 -21.398 < 0.001 -1.290 -1.013 .392 2.549

Exposure for Tanzania .384 .135 .023 2.838 .005 .035 .732 .564 1.772

Country - Myanmar -.656 .074 -.070 -8.847 < 0.001 -.847 -.465 .605 1.654

Exposure for Myanmar .432 .265 .011 1.632 .103 -.250 1.113 .844 1.184






Location – Urban -.253 .030 -.057 -8.460 < 0.001 -.329 -.176 .813 1.230

Age groups - 25-34 .401 .037 .087 10.781 < 0.001 .305 .496 .573 1.744

Age groups - 35-44 .576 .045 .106 12.910 < 0.001 .461 .691 .560 1.784

Age groups - 45-54 .821 .051 .126 16.082 < 0.001 .690 .953 .614 1.628

Age groups - 55-64 .940 .061 .114 15.428 < 0.001 .783 1.098 .682 1.465

Age groups - 65+ 1.034 .071 .106 14.626 < 0.001 .852 1.216 .711 1.406







Marital Status - Single -.486 .037 -.108 -13.271 < 0.001 -.581 -0.392 .565 1.769

Marital Status - Married, not living with spouse -.075 .062 -.008 -1.201 .230 -.236 0.086 .939 1.065






4.1.4.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.25% 1.38% 5.48% 0.00% 1.646

53


54

4.2 Regression models – Knowledge



The model includes 23621 observations. Missing data were handled using pair wise deletion. 18320


Table 79 - Model n. 1 summary - Knowledge

Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001

2 0.378 0.143 0.143 2.336 0.098 542.636 4 18952 < 0.001

3 0.463 0.215 0.213 2.238 0.071 68.819 25 18927 < 0.001

4.2.1.2 ANOVA

Table 80 - Model n. 1 ANOVA - Knowledge

Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 5442.977 1 5442.977 894.832 < 0.001

Residual 115303.239 18956 6.083

Total 120746.216 18957

2

Regression 17291.491 5 3458.298 633.530 < 0.001

Residual 103454.726 18952 5.459

Total 120746.216 18957

3

Regression 25911.948 30 863.732 172.383 < 0.001

Residual 94834.268 18927 5.011

Total 120746.216 18957






55

Table 81 - Model n. 1 regression coefficients - Knowledge

Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.353 .090 26.023 < 0.001 2.120 2.586


programme .653 .044 .102 14.721 < 0.001 .539 .767 .865 1.156




Interest in politics - Somewhat interested 1.313 .053 .247 24.685 < 0.001 1.176 1.450 .414 2.414


Country - Bangladesh .686 .071 .086 9.725 < 0.001 .504 .867 .534 1.874

Country - Nepal 0.105 .062 .016 1.694 .090 -0.054 0.264 .493 2.029

Country - Kenya .270 .063 .036 4.297 < 0.001 .108 .431 .605 1.653

Country - Nigeria .116 .059 .018 1.971 .049 -0.036 .268 .516 1.936

Country - Tanzania -.269 .061 -.040 -4.398 < 0.001 -0.426 -.111 .492 2.031

Country - Myanmar -1.216 .088 -.107 -13.768 < 0.001 -1.443 -.988 .690 1.450

Location – Urban .119 .038 .022 3.151 .002 .022 .217 .819 1.221

Age groups - 25-34 .231 .047 .042 4.898 < 0.001 .110 .353 .573 1.744

Age groups - 35-44 .364 .057 .055 6.417 < 0.001 .218 .510 .561 1.783

Age groups - 45-54 .364 .065 .046 5.602 < 0.001 .197 .531 .614 1.628

Age groups - 55-64 .402 .078 .040 5.189 < 0.001 .203 0.602 .683 1.465

Age groups - 65+ .385 .090 .033 4.286 < 0.001 .154 0.617 .711 1.406



Education - Completed secondary 1.007 .057 .188 17.811 < 0.001 .862 1.153 .372 2.687

Education - Completed college or university 1.680 .068 .241 24.883 < 0.001 1.506 1.854 .443 2.259

Income - Low (can afford food at most) -.034 .043 -.006 -0.787 .431 -.143 .076 .777 1.287

Income - High (can afford almost everything) .144 .061 .016 2.369 .018 -.013 .301 .869 1.151

Marital Status - Single -.128 .047 -.024 -2.756 .006 -.248 -.008 .566 1.767

Marital Status - Married, not living with spouse -.035 .079 -.003 -.443 .658 -.240 .169 .939 1.065





Marital Status - Living with partner .489 .192 .017 2.541 .011 -.007 .984 .970 1.031

4.2.1.4 Diagnostics

Table 82 - Model n. 1 diagnostics - Knowledge

N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.00% 0.56% 5.15% 0.00% 1.616

56

Figure 13 - Residuals and predicted values - Model n. 1 - Knowledge




Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001

2 0.378 0.143 0.143 2.336 0.098 542.636 4 18952 < 0.001

3 0.463 0.215 0.213 2.238 0.071 68.819 25 18927 < 0.001

57

4.2.2.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 5442.977 1 5442.977 894.832 < 0.001

Residual 115303.239 18956 6.083

Total 120746.216 18957

2

Regression 6534.235 3 2178.078 361.462 < 0.001

Residual 114211.981 18954 6.026

Total 120746.216 18957

3

Regression 17626.923 7 2518.132 462.751 < 0.001

Residual 103119.293 18950 5.442

Total 120746.216 18957

4

Regression 25912.372 31 835.883 166.817 < 0.001

Residual 94833.844 18926 5.011

Total 120746.216 18957






58


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.356 .091 25.957 < 0.001 2.122 2.589


programme .643 .056 .100 11.417 < 0.001 .498 .788 .537 1.862


Exposure*Sex - Exposure for women .026 .089 .003 0.291 .771 -.204 .256 .536 1.865






Country - Nepal 0.106 .062 .016 1.707 .088 -0.054 0.265 .492 2.035

Country - Kenya .270 .063 .036 4.298 < 0.001 .108 .431 .605 1.653

Country - Nigeria .116 .059 .018 1.966 .049 -0.036 .268 .516 1.937


Country - Myanmar -1.216 .088 -.107 -13.766 < 0.001 -1.443 -.988 .690 1.450

Location – Urban .119 .038 .022 3.153 .002 .022 .217 .819 1.221

Age groups - 25-34 .232 .047 .042 4.901 < 0.001 .110 .353 .573 1.744

Age groups - 35-44 .365 .057 .055 6.422 < 0.001 .218 .511 .560 1.784

Age groups - 45-54 .364 .065 .046 5.608 < 0.001 .197 .532 .614 1.629

Age groups - 55-64 .402 .078 .040 5.192 < 0.001 .203 0.602 .683 1.465

Age groups - 65+ .385 .090 .033 4.284 < 0.001 .153 0.617 .711 1.406







Marital Status - Single -.128 .047 -.024 -2.756 .006 -.248 -.008 .566 1.767







4.2.2.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.00% 0.56% 5.13% 0.00% 1.616

59





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001

2 0.221 0.049 0.048 2.462 0.004 7.184 10 18946 < 0.001

3 0.35 0.123 0.122 2.365 0.074 199.513 8 18938 < 0.001

4 0.448 0.201 0.200 2.258 0.078 307.718 6 18932 < 0.001

5 0.45 0.203 0.201 2.255 0.002 11.632 4 18928 < 0.001

6 0.479 0.230 0.228 2.218 0.027 44.330 15 18913 < 0.001

60

4.2.3.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 5442.977 1 5442.977 894.832 < 0.001

Residual 115303.239 18956 6.083

Total 120746.216 18957

2

Regression 5878.520 11 534.411 88.144 < 0.001

Residual 114867.696 18946 6.063

Total 120746.216 18957

3

Regression 14807.112 19 779.322 139.314 < 0.001

Residual 105939.104 18938 5.594

Total 120746.216 18957

4

Regression 24220.583 25 968.823 190.020 < 0.001

Residual 96525.633 18932 5.099

Total 120746.216 18957

5

Regression 24457.279 29 843.354 165.782 < 0.001

Residual 96288.937 18928 5.087

Total 120746.216 18957

6

Regression 27727.637 44 630.174 128.130 < 0.001

Residual 93018.579 18913 4.918

Total 120746.216 18957







61


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 1.743 .098 17.771 < 0.001 1.491 1.996


programme 3.984 .214 .622 18.636 < 0.001 3.433 4.534 .037 27.352


Age groups - 25-34 .298 .053 .054 5.623 < 0.001 .162 .435 .447 2.240

Exposure for 25-34 -.221 .119 -.019 -1.855 .064 -.527 .086 .370 2.703

Age groups - 35-44 .516 .063 .078 8.163 < 0.001 .353 .678 .444 2.250

Exposure for 35-44 -.522 .137 -.036 -3.801 < 0.001 -.876 -.168 .453 2.208

Age groups - 45-54 .554 .073 .070 7.594 < 0.001 .366 .742 .478 2.093

Exposure for 45-54 -.689 .157 -.039 -4.392 < 0.001 -1.094 -.285 .506 1.978

Age groups - 55-64 .585 .086 .059 6.807 < 0.001 .364 .807 .544 1.837

Exposure for 55-64 -.644 .199 -.026 -3.232 .001 -1.157 -.131 .623 1.606

Age groups - 65+ .601 .098 .051 6.163 < 0.001 .350 .853 .592 1.688

Exposure for 65 or more -.733 .260 -.021 -2.822 .005 -1.401 -.064 .717 1.394


Exposure for Literate -1.128 .209 -.057 -5.391 < 0.001 -1.667 -.589 .360 2.778

Education - Completed primary .958 .066 .157 14.562 < 0.001 .789 1.128 .350 2.855

Exposure for Primary -1.781 .193 -.106 -9.210 < 0.001 -2.279 -1.282 .306 3.269

Education - Completed secondary 1.377 .065 .257 21.052 < 0.001 1.208 1.545 .273 3.661

Exposure for Secondary -1.806 .176 -.178 -10.274 < 0.001 -2.259 -1.353 .136 7.339


Exposure for High educated -2.070 .195 -.166 -10.620 < 0.001 -2.572 -1.568 .167 5.983


Interest in politics - Not very interested .883 .061 .149 14.508 < 0.001 .726 1.040 .386 2.592

Exposure for Not very interested -2.358 .221 -.146 -10.658 < 0.001 -2.928 -1.788 .216 4.631


Exposure for Somewhat interested -1.840 .207 -.174 -8.896 < 0.001 -2.373 -1.307 .106 9.445


Exposure for Very interested -1.672 .210 -.174 -7.966 < 0.001 -2.212 -1.131 .086 11.664


Country - Nepal .140 .061 .021 2.287 .022 -.018 .298 .490 2.040

Country - Kenya .269 .062 .036 4.325 < 0.001 .109 .430 .603 1.659

Country - Nigeria .112 .059 .017 1.911 .056 -.039 .263 .512 1.955

Country - Tanzania -.189 .061 -.028 -3.100 .002 -.345 -.032 .487 2.054

Country - Myanmar -1.168 .088 -.103 -13.274 < 0.001 -1.394 -.941 .682 1.466

Location – Urban .138 .038 .026 3.682 < 0.001 .042 .235 .815 1.227

Income - Low (can afford food at most) -.164 .047 -.028 -3.513 < 0.001 -.284 -.044 .638 1.568

Exposure for Low income .479 .115 .035 4.162 < 0.001 .182 .775 .578 1.729


Exposure for High income .239 .142 .014 1.680 .093 -.128 .606 .580 1.725

Marital Status - Single -.097 .046 -.018 -2.088 .037 -.216 .023 .561 1.781





has more than on wife .465 .172 .018 2.704 .007 .022 0.908 .913 1.095


4.2.3.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.01% 0.74% 5.32% 0.00% 1.623

62





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001

2 0.28 0.079 0.078 2.424 0.033 57.274 12 18944 < 0.001

3 0.418 0.175 0.174 2.293 0.096 553.673 4 18940 < 0.001

4 0.467 0.218 0.216 2.234 0.043 54.372 19 18921 < 0.001

63

4.2.4.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 5442.977 1 5442.977 894.832 < 0.001

Residual 115303.239 18956 6.083

Total 120746.216 18957

2

Regression 9479.734 13 729.21 124.154 < 0.001

Residual 111266.482 18944 5.873

Total 120746.216 18957

3

Regression 21128.254 17 1242.838 236.296 < 0.001

Residual 99617.962 18940 5.260

Total 120746.216 18957

4

Regression 26285.744 36 730.160 146.255 < 0.001

Residual 94460.472 18921 4.992

Total 120746.216 18957






(VIF) is 1.934.

64


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 2.167 .094 22.986 < 0.001 1.924 2.410


programme 1.247 .098 .195 12.767 < 0.001 .995 1.499 .178 5.625

Country - Bangladesh .834 .078 .104 10.762 < 0.001 .634 1.034 .440 2.272

Exposure for Bangladesh -.331 .204 -.013 -1.619 .106 -.858 .196 .652 1.533

Country - Nepal .420 .073 .062 5.739 < 0.001 .232 .609 .349 2.866

Exposure for Nepal -1.157 .143 -.091 -8.069 < 0.001 -1.527 -.788 .328 3.052

Country - Kenya .439 .070 .058 6.299 < 0.001 .259 .618 .489 2.043

Exposure for Kenya -.753 .200 -.030 -3.772 < 0.001 -1.268 -.239 .651 1.536

Country - Nigeria .269 .071 .041 3.805 < 0.001 .087 .451 .358 2.792

Exposure for Nigeria -.620 .137 -.054 -4.512 < 0.001 -.974 -.266 .292 3.425

Country - Tanzania -.061 .068 -.009 -0.888 .375 -.237 .115 .392 2.549

Exposure for Tanzania -.955 .172 -.048 -5.564 < 0.001 -1.397 -.513 .564 1.772

Country - Myanmar -1.049 .094 -.092 -11.140 < 0.001 -1.291 -.806 .605 1.654

Exposure for Myanmar -.420 .336 -.009 -1.250 .211 -1.285 .445 .844 1.184






Location – Urban .126 .038 .024 3.336 .001 .029 .224 .813 1.230

Age groups - 25-34 .229 .047 .041 4.859 < 0.001 .108 .351 .573 1.744

Age groups - 35-44 .371 .057 .056 6.544 < 0.001 .225 .517 .560 1.784

Age groups - 45-54 .366 .065 .046 5.652 < 0.001 .199 .533 .614 1.628

Age groups - 55-64 .401 .077 .040 5.184 < 0.001 .202 .601 .682 1.465

Age groups - 65+ .378 .090 .032 4.216 < 0.001 .147 .609 .711 1.406






Income - High (can afford almost everything) .161 .061 .018 2.639 .008 .004 .317 .868 1.152

Marital Status - Single -.123 .047 -.023 -2.642 .008 -.243 -0.003 .565 1.769







4.2.4.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.00% 0.58% 5.19% 0.00% 1.62

65


66

4.3 Regression models – Discussion





Table 95 - Model n. 1 summary - Discussion

Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001

2 0.398 0.158 0.158 1.917 0.123 690.582 4 18952 < 0.001

3 0.538 0.289 0.288 1.762 0.131 139.471 25 18927 < 0.001

4.3.1.2 ANOVA

Table 96 - Model n. 1 ANOVA - Discussion

Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 2922.807 1 2922.807 694.622 < 0.001

Residual 79762.372 18956 4.208

Total 82685.180 18957

2

Regression 13069.555 5 2613.911 711.605 < 0.001

Residual 69615.625 18952 3.673

Total 82685.180 18957

3

Regression 23899.267 30 796.642 256.491 < 0.001

Residual 58785.912 18927 3.106

Total 82685.180 18957






67

Table 97 - Model n. 1 regression coefficients - Discussion

Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 3.618 .100 36.315 < 0.001 3.362 3.875


programme .470 .049 .066 9.624 < 0.001 .344 .596 .865 1.156




Interest in politics - Somewhat interested 1.147 .059 .193 19.573 < 0.001 .996 1.298 .414 2.414


Country - Bangladesh -1.873 .078 -.209 -24.101 < 0.001 -2.073 -1.672 .534 1.874

Country - Nepal -1.442 .068 -.192 -21.198 < 0.001 -1.617 -1.267 .493 2.029

Country - Kenya -.506 .069 -.060 -7.324 < 0.001 -.684 -.328 .605 1.653

Country - Nigeria -.586 .065 -.080 -9.024 < 0.001 -0.753 -.419 .516 1.936


Country - Myanmar -2.984 .097 -.234 -30.669 < 0.001 -3.235 -2.733 .690 1.450

Location – Urban -.022 .042 -.004 -0.539 .590 -.130 .085 .819 1.221

Age groups - 25-34 .220 .052 .035 4.222 < 0.001 .086 .354 .573 1.744

Age groups - 35-44 .336 .063 .046 5.377 < 0.001 .175 .497 .561 1.783

Age groups - 45-54 .392 .072 .044 5.475 < 0.001 .207 .576 .614 1.628

Age groups - 55-64 .311 .085 .028 3.638 < 0.001 .091 0.531 .683 1.465

Age groups - 65+ .265 .099 .020 2.672 .008 .010 0.520 .711 1.406

Education - Literate .229 .069 .027 3.306 .001 .051 .407 .604 1.655



Education - Completed college or university 1.119 .074 .143 15.034 < 0.001 .927 1.310 .443 2.259

Income - Low (can afford food at most) -.139 .047 -.021 -2.949 .003 -.260 -.018 .777 1.287





Marital Status - Widowed -.423 .097 -.030 -4.381 < 0.001 -.672 -.174 .877 1.140


has more than on wife 1.459 .187 .051 7.795 < 0.001 .977 1.942 .953 1.049

Marital Status - Living with partner -.237 .212 -.007 -1.119 .263 -.783 .309 .970 1.031

4.3.1.4 Diagnostics

Table 98 - Model n. 1 diagnostics - Discussion

N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.02% 0.48% 4.99% 0.00% 1.666

68

Figure 17 - Residuals and predicted values - Model n. 1 - Discussion




Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001

2 0.221 0.049 0.049 2.752 0.018 183.511 2 18954 < 0.001

3 0.404 0.163 0.163 2.581 0.115 648.597 4 18950 < 0.001

4 0.487 0.237 0.236 2.466 0.074 76.230 24 18926 < 0.001

69

4.3.2.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 4577.069 1 4577.069 592.956 < 0.001

Residual 146322.657 18956 7.719

Total 150899.727 18957

2

Regression 7356.616 3 2452.205 323.799 < 0.001

Residual 143543.111 18954 7.573

Total 150899.727 18957

3

Regression 24642.158 7 3520.308 528.363 < 0.001

Residual 126257.568 18950 6.663

Total 150899.727 18957

4

Regression 35771.348 31 1153.914 189.692 < 0.001

Residual 115128.379 18926 6.083

Total 150899.727 18957






70


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 3.621 .100 36.210 < 0.001 3.363 3.878


programme .460 .062 .064 7.417 < 0.001 .300 .620 .537 1.862





Interest in politics - Somewhat interested 1.147 .059 .193 19.544 < 0.001 .995 1.298 .413 2.419



Country - Nepal -1.441 .068 -.192 -21.153 < 0.001 -1.617 -1.266 .492 2.035

Country - Kenya -.506 .069 -.060 -7.323 < 0.001 -.684 -.328 .605 1.653

Country - Nigeria -.586 .065 -.080 -9.027 < 0.001 -0.754 -.419 .516 1.937


Country - Myanmar -2.984 .097 -.234 -30.666 < 0.001 -3.235 -2.733 .690 1.450

Location – Urban -.022 .042 -.004 -0.537 .591 -.130 .085 .819 1.221

Age groups - 25-34 .220 .052 .035 4.225 < 0.001 .086 .354 .573 1.744

Age groups - 35-44 .337 .063 .046 5.382 < 0.001 .176 .498 .560 1.784

Age groups - 45-54 .392 .072 .044 5.480 < 0.001 .208 .577 .614 1.629

Age groups - 55-64 .311 .085 .028 3.641 < 0.001 .091 0.531 .683 1.465

Age groups - 65+ .264 .099 .020 2.671 .008 .009 0.520 .711 1.406














4.3.2.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.02% 0.48% 5.00% 0.00% 1.666

71





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001

2 0.22 0.049 0.048 2.752 0.018 362.710 1 18955 < 0.001

3 0.231 0.054 0.053 2.745 0.005 20.043 5 18950 < 0.001

4 0.299 0.089 0.088 2.694 0.036 92.561 8 18942 < 0.001

5 0.38 0.144 0.143 2.611 0.055 1217.386 1 18941 < 0.001

6 0.429 0.184 0.183 2.550 0.040 155.280 6 18935 < 0.001

7 0.489 0.239 0.238 2.464 0.055 90.759 15 18920 < 0.001

72

4.3.3.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 4577.069 1 4577.069 592.956 < 0.001

Residual 146322.657 18956 7.719

Total 150899.727 18957

2

Regression 7324.427 2 3662.213 483.490 < 0.001

Residual 143575.300 18955 7.575

Total 150899.727 18957

3

Regression 8079.702 7 1154.243 153.150 < 0.001

Residual 142820.024 18950 7.537

Total 150899.727 18957

4

Regression 13452.855 15 896.857 123.599 < 0.001

Residual 137446.871 18942 7.256

Total 150899.727 18957

5

Regression 21753.418 16 1359.589 199.402 < 0.001

Residual 129146.309 18941 6.818

Total 150899.727 18957

6

Regression 27809.954 22 1264.089 194.456 < 0.001

Residual 123089.772 18935 6.501

Total 150899.727 18957

7

Regression 36072.322 37 974.928 160.638 < 0.001

Residual 114827.405 18920 6.069

Total 150899.727 18957







73


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 3.396 .106 31.899 < 0.001 3.121 3.670


programme 1.839 .228 .257 8.054 < 0.001 1.251 2.427 .040 25.287


Age groups - 25-34 .220 .052 .035 4.222 < 0.001 .086 .354 .572 1.748

Age groups - 35-44 .343 .063 .047 5.483 < 0.001 .182 .504 .559 1.790

Age groups - 45-54 .394 .072 .045 5.494 < 0.001 .209 .578 .612 1.635

Age groups - 55-64 .318 .085 .029 3.725 < 0.001 .098 .538 .681 1.469

Age groups - 65+ .281 .099 .021 2.834 .005 .026 .537 .707 1.414


Exposure for Literate -.139 .231 -.006 -0.602 .547 -.733 .455 .366 2.733


Exposure for Primary -.374 .213 -.020 -1.760 .078 -.922 .174 .312 3.204

Education - Completed secondary .923 .071 .154 12.952 < 0.001 .740 1.107 .284 3.524

Exposure for Secondary -.586 .190 -.052 -3.087 .002 -1.075 -.097 .144 6.941


Exposure for High educated -.470 .205 -.034 -2.291 .022 -.999 .059 .186 5.379



Exposure for Not very interested -1.331 .243 -.074 -5.465 < 0.001 -1.958 -.703 .220 4.544


Exposure for Somewhat interested -1.096 .228 -.093 -4.817 < 0.001 -1.682 -.510 .108 9.263


Exposure for Very interested -1.009 .229 -.094 -4.404 < 0.001 -1.600 -.419 .089 11.272


Country - Nepal -1.436 .068 -.191 -21.082 < 0.001 -1.612 -1.261 .490 2.039

Country - Kenya -.499 .069 -.059 -7.218 < 0.001 -.677 -.321 .604 1.657

Country - Nigeria -.571 .065 -.078 -8.784 < 0.001 -.738 -.403 .515 1.943

Country - Tanzania -.694 .068 -.093 -10.270 < 0.001 -.868 -.520 .488 2.050

Country - Myanmar -2.937 .098 -.231 -30.112 < 0.001 -3.189 -2.686 .685 1.460

Location – Urban -.013 .042 -.002 -0.303 .762 -.120 .095 .816 1.225


Income - High (can afford almost everything) .011 .067 .001 0.164 .870 -.162 0.184 .869 1.151








4.3.3.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.02% 0.48% 5.04% 0.00% 1.667

74





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001

2 0.377 0.142 0.141 2.614 0.112 205.419 12 18944 < 0.001

3 0.462 0.214 0.213 2.503 0.072 432.609 4 18940 < 0.001

4 0.49 0.240 0.239 2.462 0.026 34.312 19 18921 < 0.001

75

4.3.4.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 4577.069 1 4577.069 592.956 < 0.001

Residual 146322.657 18956 7.719

Total 150899.727 18957

2

Regression 21424.612 13 1648.047 241.132 < 0.001

Residual 129475.114 18944 6.835

Total 150899.727 18957

3

Regression 32263.687 17 1897.864 302.990 < 0.001

Residual 118636.040 18940 6.264

Total 150899.727 18957

4

Regression 36215.122 36 1005.976 165.969 < 0.001

Residual 114684.605 18921 6.061

Total 150899.727 18957






(VIF) is 1.934.

76


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 3.763 .104 36.226 < 0.001 3.495 4.030


programme .054 .108 .008 0.502 .616 -.223 .331 .178 5.625


Exposure for Bangladesh .380 .225 .013 1.688 .091 -.200 .961 .652 1.533

Country - Nepal -1.758 .081 -.234 -21.781 < 0.001 -1.966 -1.550 .349 2.866

Exposure for Nepal 1.130 .158 .079 7.147 < 0.001 .722 1.537 .328 3.052

Country - Kenya -.647 .077 -.076 -8.438 < 0.001 -.845 -.450 .489 2.043

Exposure for Kenya .824 .220 .029 3.745 < 0.001 .257 1.391 .651 1.536

Country - Nigeria -.589 .078 -.080 -7.567 < 0.001 -.790 -.389 .358 2.792

Exposure for Nigeria .115 .151 .009 0.760 .447 -.275 .505 .292 3.425


Exposure for Tanzania .448 .189 .020 2.366 .018 -.040 .935 .564 1.772

Country - Myanmar -3.145 .104 -.247 -30.317 < 0.001 -3.413 -2.878 .605 1.654

Exposure for Myanmar .940 .370 .018 2.539 .011 -.014 1.893 .844 1.184






Location – Urban -.043 .042 -.007 -1.040 .299 -.151 .064 .813 1.230

Age groups - 25-34 .223 .052 .036 4.293 < 0.001 .089 .357 .573 1.744

Age groups - 35-44 .330 .062 .045 5.279 < 0.001 .169 .491 .560 1.784

Age groups - 45-54 .388 .071 .044 5.426 < 0.001 .204 .572 .614 1.628

Age groups - 55-64 .312 .085 .028 3.664 < 0.001 .093 .532 .682 1.465

Age groups - 65+ .273 .099 .021 2.760 .006 .018 .528 .711 1.406







Marital Status - Single -.219 .051 -.036 -4.266 < 0.001 -.351 -0.087 .565 1.769





has more than on wife 1.541 .188 .054 8.188 < 0.001 1.056 2.026 .940 1.064


4.3.4.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.02% 0.44% 5.05% 0.00% 1.669

77


78

4.4 Regression models – Efficacy





Table 111 - Model n. 1 summary - Efficacy

Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117

2 0.174 0.030 0.030 1.875 0.030 147.891 4 18952 < 0.001

3 0.331 0.110 0.108 1.798 0.079 67.432 25 18927 < 0.001

4.4.1.2 ANOVA

Table 112 - Model n. 1 ANOVA - Efficacy

Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 8.913 1 8.913 2.459 0.117

Residual 68697.039 18956 3.624

Total 68705.952 18957

2

Regression 2088.300 5 417.660 118.820 < 0.001

Residual 66617.652 18952 3.515

Total 68705.952 18957

3

Regression 7536.543 30 251.218 77.732 < 0.001

Residual 61169.409 18927 3.232

Total 68705.952 18957






79

Table 113 - Model n. 1 regression coefficients - Efficacy

Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 4.441 .073 61.152 < 0.001 4.254 4.628


programme .097 .036 .020 2.713 .007 .005 .188 .865 1.156

Sex of the respondent – Female -.025 .028 -.007 -0.898 .369 -.096 .046 .892 1.121


Interest in politics - Not very interested .140 .044 .031 3.146 .002 .025 .254 .478 2.094



Country - Bangladesh 1.468 .057 .243 25.917 < 0.001 1.322 1.614 .534 1.874

Country - Nepal 0.343 .050 .068 6.921 < 0.001 0.215 0.471 .493 2.029

Country - Kenya .549 .050 .096 10.896 < 0.001 .419 .679 .605 1.653

Country - Nigeria -.271 .047 -.055 -5.720 < 0.001 -0.393 -.149 .516 1.936

Country - Tanzania .239 .049 .048 4.875 < 0.001 0.113 .366 .492 2.031

Country - Myanmar 1.645 .071 .191 23.189 < 0.001 1.462 1.827 .690 1.450

Location – Urban -.140 .030 -.035 -4.614 < 0.001 -.218 -.062 .819 1.221

Age groups - 25-34 -.002 .038 -.001 -0.063 .950 -.100 .095 .573 1.744

Age groups - 35-44 .022 .046 .004 0.488 .625 -.095 .140 .561 1.783

Age groups - 45-54 .057 .052 .010 1.097 .273 -.077 .192 .614 1.628

Age groups - 55-64 .078 .062 .010 1.258 .208 -.082 0.239 .683 1.465

Age groups - 65+ .187 .072 .021 2.592 .010 .001 0.373 .711 1.406

Education - Literate -.106 .050 -.019 -2.098 .036 -.236 .024 .604 1.655

Education - Completed primary .070 .047 .015 1.470 .141 -.052 .192 .443 2.255

Education - Completed secondary .054 .045 .013 1.194 .232 -.063 .171 .372 2.687

Education - Completed college or university -.103 .054 -.020 -1.893 .058 -.242 .037 .443 2.259




Marital Status - Married, not living with spouse -.261 .064 -.029 -4.083 < 0.001 -.425 -.096 .939 1.065

Marital Status - Divorced/Separated .072 .099 .005 0.729 .466 -.183 .327 .961 1.040



has more than on wife -.101 .136 -.005 -0.738 .460 -.452 0.251 .953 1.049

Marital Status - Living with partner -.027 .154 -.001 -.175 .861 -.425 .371 .970 1.031

4.4.1.4 Diagnostics

Table 114 - Model n. 1 diagnostics - Efficacy

N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.12% 1.15% 5.79% 0.00% 1.614

80

Figure 21 - Residuals and predicted values - Model n. 1 - Efficacy




Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117

2 0.035 0.001 0.001 1.903 0.001 10.336 2 18954 < 0.001

3 0.175 0.030 0.030 1.875 0.029 143.073 4 18950 < 0.001

4 0.331 0.110 0.108 1.798 0.079 70.199 24 18926 < 0.001

81

4.4.2.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 8.913 1 8.913 2.459 0.117

Residual 68697.039 18956 3.624

Total 68705.952 18957

2

Regression 83.752 3 27.917 7.711 < 0.001

Residual 68622.200 18954 3.62

Total 68705.952 18957

3

Regression 2095.399 7 299.343 85.160 < 0.001

Residual 66610.553 18950 3.515

Total 68705.952 18957

4

Regression 7540.330 31 243.236 75.263 < 0.001

Residual 61165.622 18926 3.232

Total 68705.952 18957






82


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 4.448 .073 61.030 < 0.001 4.260 4.636


programme .066 .045 .014 1.470 .141 -.050 .183 .537 1.862








Country - Nepal 0.346 .050 .068 6.969 < 0.001 0.218 0.474 .492 2.035

Country - Kenya .549 .050 .096 10.900 < 0.001 .419 .679 .605 1.653

Country - Nigeria -.272 .047 -.055 -5.737 < 0.001 -0.394 -.150 .516 1.937

Country - Tanzania .239 .049 .048 4.872 < 0.001 0.113 .365 .492 2.031

Country - Myanmar 1.645 .071 .192 23.195 < 0.001 1.462 1.828 .690 1.450

Location – Urban -.140 .030 -.035 -4.604 < 0.001 -.218 -.062 .819 1.221

Age groups - 25-34 -.002 .038 .000 -0.050 .960 -.100 .096 .573 1.744

Age groups - 35-44 .023 .046 .005 0.514 .607 -.094 .141 .560 1.784

Age groups - 45-54 .059 .052 .010 1.125 .261 -.076 .193 .614 1.629

Age groups - 55-64 .079 .062 .011 1.272 .203 -.081 0.240 .683 1.465

Age groups - 65+ .187 .072 .021 2.586 .010 .001 0.373 .711 1.406














4.4.2.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.12% 1.14% 5.79% 0.00% 1.614

83





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117

2 0.172 0.030 0.029 1.876 0.029 95.867 6 18950 < 0.001

3 0.186 0.035 0.034 1.871 0.005 9.671 10 18940 < 0.001

4 0.19 0.036 0.035 1.870 0.002 7.625 4 18936 < 0.001

5 0.335 0.112 0.111 1.795 0.076 85.615 19 18917 < 0.001

84

4.4.3.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 8.913 1 8.913 2.459 0.117

Residual 68697.039 18956 3.624

Total 68705.952 18957

2

Regression 2032.693 7 290.385 82.534 < 0.001

Residual 66673.259 18950 3.518

Total 68705.952 18957

3

Regression 2371.390 17 139.494 39.829 < 0.001

Residual 66334.562 18940 3.502

Total 68705.952 18957

4

Regression 2478.059 21 118.003 33.740 < 0.001

Residual 66227.893 18936 3.497

Total 68705.952 18957

5

Regression 7722.103 40 193.053 59.884 < 0.001

Residual 60983.849 18917 3.224

Total 68705.952 18957







85


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 4.288 .077 55.815 < 0.001 4.090 4.486


programme .965 .149 .200 6.456 < 0.001 .580 1.350 .049 20.404


Age groups - 25-34 .061 .043 .015 1.422 .155 -.049 .171 .450 2.224

Exposure for 25-34 -.298 .095 -.035 -3.138 .002 -.543 -.053 .379 2.636

Age groups - 35-44 .091 .051 .018 1.779 .075 -.041 .222 .448 2.232

Exposure for 35-44 -.290 .110 -.027 -2.648 .008 -.573 -.008 .466 2.146

Age groups - 45-54 .146 .059 .024 2.475 .013 -.006 .297 .482 2.073

Exposure for 45-54 -.390 .125 -.030 -3.121 .002 -.712 -.068 .523 1.912

Age groups - 55-64 .142 .069 .019 2.047 .041 -.037 .320 .551 1.816

Exposure for 55-64 -.254 .159 -.014 -1.595 .111 -.663 .156 .641 1.560

Age groups - 65+ .301 .079 .034 3.832 < 0.001 .099 .504 .599 1.670

Exposure for 65 or more -.619 .207 -.024 -2.995 .003 -1.151 -.087 .743 1.346







Exposure for Not very interested -.907 .177 -.075 -5.130 < 0.001 -1.363 -.452 .222 4.513


Exposure for Somewhat interested -.813 .164 -.102 -4.947 < 0.001 -1.236 -.389 .110 9.087

Interest in politics - Very interested .904 .052 .213 17.313 < 0.001 .769 1.038 .311 3.213

Exposure for Very interested -.745 .166 -.103 -4.499 < 0.001 -1.172 -.318 .090 11.082


Country - Nepal .338 .050 .067 6.826 < 0.001 .211 .466 .492 2.033

Country - Kenya .550 .050 .096 10.914 < 0.001 .420 .680 .604 1.657

Country - Nigeria -.275 .048 -.055 -5.783 < 0.001 -.397 -.152 .512 1.954

Country - Tanzania .252 .049 .050 5.126 < 0.001 .125 .379 .489 2.045

Country - Myanmar 1.653 .071 .192 23.223 < 0.001 1.469 1.836 .683 1.463

Location – Urban -.130 .030 -.033 -4.288 < 0.001 -.209 -.052 .815 1.226

Income - Low (can afford food at most) .062 .038 .014 1.638 .101 -.035 .158 .645 1.551

Exposure for Low income .239 .090 .023 2.642 .008 .006 .471 .615 1.625


Exposure for High income .105 .112 .008 0.937 .349 -.184 .394 .612 1.633

Marital Status - Single .008 .038 .002 0.216 .829 -.089 .105 .562 1.780







4.4.3.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.07% 1.15% 5.75% 0.00% 1.615

86





Model R R2 Adjusted

R2

Std. Error of

the Estimate

Change Statistics

R2


Sig. F

Change

1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117

2 0.28 0.078 0.078 1.828 0.078 133.768 12 18944 < 0.001

3 0.328 0.108 0.107 1.799 0.030 157.321 4 18940 < 0.001

4 0.336 0.113 0.111 1.795 0.005 5.410 19 18921 < 0.001

87

4.4.4.2 ANOVA


Model Sum of

Squares df

Mean

Square F Sig.

1

Regression 8.913 1 8.913 2.459 0.117

Residual 68697.039 18956 3.624

Total 68705.952 18957

2

Regression 5375.224 13 413.479 123.683 < 0.001

Residual 63330.728 18944 3.343

Total 68705.952 18957

3

Regression 7411.728 17 435.984 134.720 < 0.001

Residual 61294.224 18940 3.236

Total 68705.952 18957

4

Regression 7742.911 36 215.081 66.754 < 0.001

Residual 60963.041 18921 3.222

Total 68705.952 18957






(VIF) is 1.934.

88


Coefficients

t Sig.

99% Confidence

Interval for B

Collinearity

Statistics


Bound

Upper

Bound Tolerance VIF

(Constant) 4.295 .076 56.718 < 0.001 4.100 4.490


programme .543 .078 .112 6.918 < 0.001 .341 .745 .178 5.625


Exposure for Bangladesh -.835 .164 -.043 -5.083 < 0.001 -1.258 -.412 .652 1.533

Country - Nepal .564 .059 .111 9.578 < 0.001 .412 .715 .349 2.866

Exposure for Nepal -.796 .115 -.083 -6.904 < 0.001 -1.092 -.499 .328 3.052

Country - Kenya .680 .056 .119 12.152 < 0.001 .536 .824 .489 2.043

Exposure for Kenya -.611 .160 -.032 -3.806 < 0.001 -1.024 -.197 .651 1.536

Country - Nigeria -.189 .057 -.038 -3.330 .001 -.335 -.043 .358 2.792

Exposure for Nigeria -.359 .110 -.041 -3.249 .001 -.643 -.074 .292 3.425

Country - Tanzania .387 .055 .077 7.060 < 0.001 .246 .529 .392 2.549

Exposure for Tanzania -.628 .138 -.042 -4.556 < 0.001 -.984 -.273 .564 1.772

Country - Myanmar 1.812 .076 .211 23.950 < 0.001 1.617 2.006 .605 1.654

Exposure for Myanmar -.997 .270 -.028 -3.695 < 0.001 -1.692 -.302 .844 1.184




Interest in politics - Very interested .807 .046 .190 17.591 < 0.001 .689 .925 .403 2.482


Location – Urban -.128 .030 -.032 -4.202 < 0.001 -.206 -.049 .813 1.230

Age groups - 25-34 -.004 .038 -.001 -0.103 .918 -.102 .094 .573 1.744

Age groups - 35-44 .026 .046 .005 0.568 .570 -.091 .143 .560 1.784

Age groups - 45-54 .058 .052 .010 1.113 .266 -.076 .192 .614 1.628

Age groups - 55-64 .076 .062 .010 1.215 .225 -.085 .236 .682 1.465

Age groups - 65+ .182 .072 .021 2.524 .012 -.004 .368 .711 1.406







Marital Status - Single -.003 .037 -.001 -0.076 .939 -.099 0.093 .565 1.769

Marital Status - Married, not living with spouse -.258 .064 -.029 -4.045 < 0.001 -.422 -0.094 .939 1.065




has more than on wife -.195 .137 -.010 -1.424 .155 -.549 .158 .940 1.064


4.4.4.4 Diagnostics


N. of

cases

N.

predicted

scores

Std

residuals

> |3.29|

Std

residuals

> |2.58|

Std

residuals

> |1.96|

Cook's

distance

above |1|

Durbin-

Watson

statistic

23621 18320 0.14% 1.14% 5.88% 0.00% 1.617

89


Political Participation and the Media -...

Documents

Transcript of Political Participation and the Media -...