Centre for Market and Public Organisation Measuring socio-economic position in ALSPAC Liz Washbrook,...

Centre for Market and Public Organisation

Measuring socio-economic position in ALSPAC

Liz Washbrook, [email protected]

ESRC/ALSPAC Large Grant Meeting5th November 2008

mailto:[email protected]

But first! US cohort studies

Early Child Longitudinal Study – Birth Cohort (ECLS-B) 10,000 children born 2001, nationally representative when weighted Over-samples of low birth weight babies, twins, some ethnic groups (e.g. Native

Americans, Chinese) Samples from birth certificates, follow-ups at 9 months, 2 years, Fall prior to

kindergarten (~4y), Fall of kindergarten year (~5y). But no more! Data from parent CAPI, direct child assessments, child care providers and

teachers. Some resident and non-resident father questionnaires.

Early Child Longitudinal Study – Kindergarten Cohort (ECLS-K) 20,000 children starting kindergarten in 1998 (b. 1992/3) Children sampled from 1277 schools in 100 counties. Target 24 children per

school. Nationally representative when weighted. Follow ups at Fall & Spring kindergarten year (~5-6y), Fall & Spring 1st grade (~6-

7y), Spring 3rd grade (~9y), 5th grade (~11y), 8th grade (~14y) Data from direct child assessments, parental phone interviews, teacher and

school administrator questionnaires.

Data is publicly available (on CD). See http://nces.ed.gov/ECLS/index.asp

US cohort studies

Fragile Families 5000 children born 1998-2000 in large US cities Designed to follow children born to unmarried parents but includes

control sample of married parent families (~25%). Focus on deprived families – 44% mothers at baseline black, 35%

Hispanic, 27% teenagers, 79% high school or less Detailed information on fathers’ roles and involvement Parent interviews in hospital at birth, follow ups at 1, 3, 5 and 9.

Includes direct in-home child assessments. Data publicly available: www.fragilefamilies.princeton.edu/index.asp

Aims

Aim to stimulate discussion about the construction of an index of parental socio-economic position (SEP) from the ALSPAC data

Talk will cover The range of indicators available and their features Sample selection/missingness issues (multiple imputation) Combining the indictors into a single index (principal components

analysis)

Illustrated using a case study: Measures of social inequality in Key Stage 2 exam results (age 11)

Would a standard SEP variable available to all ALSPAC researchers be useful?

If so, how should it be constructed?

Input, feedback, discussion would be appreciated!

What is SEP?

Extensive literature on theories of social stratification (Galobardes, Lynch and Davey Smith, 2007; Bradley and Corwyn, 2002).

“Socially derived economic factors that influence what positions individuals or groups hold within the multiple-stratified structure of society” (Galobardes et al)

In practice researchers have used a multitude of individual indicators to measure SEP, each of which captures a different aspect of stratification

Composite SEP is a relative measure, whereas some indicators (income, education) measure absolute levels of resources. This may have implications when thinking about policy.

Why measure parental SEP?

SEP as a summary measure of ‘family background’ that defines sub-groups of the population. Social mobility/life chances Nature vs. nurture

Example: Joint CMPO project on the role of attitudes and aspirations in explaining the educational deficits of children in poverty

SEP as a way of capturing long-term access to resources over the life course, e.g. ‘permanent income’ in economics

To classify deprived or vulnerable groups in a way that captures the idea of multiple risks

As a control for confounding influences (e.g. studying the effects of smoking)? Disaggregated sets of control variables may be more appropriate

SEP indicators in ALSPAC

Included in the index:

Income

Education (mother and father)

Social class (mother and father)

Housing tenure

Local deprivation/affluence

Subjective financial hardship

Excluded:

Wealth

Employment status

Race/ethnicity

Family structure

How is the indicator constructed from multiple pieces of information? (High frequency of measurement in ALSPAC)

How is the indicator distributed? (E.g. discrete/continuous) For whom is it available? (Differential missingness) How well does it distinguish between high- and low-performing

children? (KS2 is an example – relationships will differ with different outcomes)

The sample

11 071 children with: A valid Key Stage 2 score Minimum of 2 (out of 10) non-missing SEP indicators (30% complete

cases)Sample is 69% of the eligible birth cohort (15 994 in NPD)

Key Stage 2 score derived from exam marks in English, maths and science in Year 6 (age 11). National tests compulsory in all state schools.

Test scores are averaged and normalised to mean zero, standard deviation 1 on the full eligible population of 15 994

The working sample is not randomly selectedMean KS2 (SD)

Working sample (N=11071) 0.11 (0.95)<2 SEP indicators (N=4923) -0.26 (1.05)

Household income

Measures: Take home weekly family income at 33, 47, 85, 97 months; 11 years

£ per week 33 mths 47 mths 85 mths 97 mths

<100 8.7 7.8 4.0 2.1

100-199 17.7 15.8 11.3 9.2

200-299 28.4 26.2 18.4 16.6

300-399 21.2 22.1 22.3 21.1

>400 24.0 28.2 44.0 50.9

N 8832 8655 7525 7037

Proportion of valid responses in bands:

Failure to update the bands means that the usefulness of the 85 and 97 month income measures is limited.

Household income

The age 11 income measure is better:

£ per week Valid %

< £120 2.3

£120-189 5.2

£190-239 5.5

£240-289 7.0

£290-359 11.7

£360-429 11.0

£430-479 7.1

£480-559 15.3

£560-799 20.6

>£800 14.2

N 6552

Household income

The SEP index uses:

Log average real equivalised weekly take home income at 33 & 47 mths

Median income for band imputed using FES data for households containing a child of the cohort member’s age, in the relevant year and income interval

Adjustment made for housing benefit income if respondent reports zero housing expenditures and lives in rented accommodation (predicted value from FES for HB recipients in the Southwest, varying with year, lone parent status and number under 16s in household)

Expressed in 1995 prices using All Items RPI

Equivalised using modified OECD scale

Averaged and logged

Nominal banded income at 85 months

Nominal continuous income at 11 years, using band midpoints

Average KS2, by preschool income quintiles

-0.25

-0.01

0.19

0.39

0.59

-0.14

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Q1 (18.3%)

Q2 (18.4%)

Q3 (23.1%)

Q4 (20.1%)

Q5 (20.2%)

Missing (24.3% total)

Average KS2 (std)

0.84

100%

Average KS2, by nominal income at age 7

-0.24

-0.07

0.08

0.25

0.52

-0.10

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

< £100 (4.1%)

£100-199 (11.8%)

£200-299 (19.1%)

£300-399 (23.2%)

> £400 (41.7%)


Average KS2 (std)

0.76

100%

Average KS2, by nominal income quintiles at age 11

-0.04

0.18

0.32

0.52

0.70

-0.07

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Q1 (20.5%)

Q2 (23.9%)

Q3 (23.6%)

Q4 (20.5%)

Q5 (11.4%)


Average KS2 (std)

0.73

100%

Parental education

Measures: Mother and partner reports for both spouses’ qualifications: antenatal, 61 and 97 months.

The SEP index uses maternal reports of own and partner’s highest qualification at 32 weeks gestation.

Issues

Non-response to the question is coded as no qualifications (don’t know, no quals and no partner were all possible responses)

Possible discrepancies between own and partner report

Possible changes in the identity of the partner over time

Possible changes in qualifications over time

Average KS2, by mother’s highest qualification

-0.39

0.07

0.41

0.83

-0.08

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

CSE/none (20.9%)

Voc/O-level (46.4%)

A-level (21.8%)

Degree (11.0%)


Average KS2 (std)

1.23

100%

Average KS2, by partner’s highest qualification

-0.31

0.10

0.30

0.78

-0.17

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

CSE/none (26.9%)

Voc/O-level (31.3%)

A-level (26.2%)

Degree (15.6%)


Average KS2 (std)

1.09

100%

Parental social class

Measures: Mother reports of own and partner’s occupation: antenatal, 8 and 97 months. Partner reports more frequent but not

coded.

The SEP index uses maternal reports of own and partner’s social class at 32 weeks gestation.

Question related to occupation in current or last job

Occupations coded according to 1991 SOC classification

Used to derive Registrar General’s Social Class – this is what is available in the datafiles. Hierarchical measure.

No other data on occupation is currently coded

Average KS2, by mother’s social class

-0.47

-0.20

-0.08

0.17

0.42

0.88

-0.18

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Unskilled (2.3%)

Semi-skilled (10.2%)

Skilled manual (8.2%)

Skilled non-man (44.6%)

Manag/tech (30.0%)

Professional (4.8%)


Average KS2 (std)

1.35100%

Average KS2, by partner’s social class

-0.32

-0.16

-0.04

0.32

0.37

0.72

-0.22

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Unskilled (3.0%)

Semi-skilled (10.3%)

Skilled manual (33.5%)

Skilled non-man (11.0%)

Manag/tech (32.8%)

Professional (9.5%)


Average KS2 (std)

1.04100%

Housing tenure

Measures: Mother reports of tenure: 8, 21, 33 and 61 months.

The SEP index uses a derived variable

‘Always owner-occupier’ – mortgaged/owned outright/buying from council at all 4 dates

‘Ever in social housing’ – council rented/Housing Association rented at any of 4 dates

‘Other’ – not otherwise classified and at least one valid response (other responses: private rented furnished/unfurnished, other). Includes all people with a missing value who were never observed in social housing, as well as renters.

Average KS2, by housing tenure 8-61 months

-0.42

0.15

0.37

-0.24

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Social housing ever (19.3%)

Other (31.7%)

Always owner-occ (49.0%)


Average KS2 (std)

0.79

100%

Local deprivation/affluence

Measures: Ward-level Index of Multiple Deprivation (IMD) currently matched at birth, age 5 and age 8, but postcodes

available on an annual basis

The SEP index uses the (continuous) rank of the IMD for ward at birth

IMD provided by government statistics. Derived from data in 6 domains: income, education, employment, housing, health, access to services

Wards in England (approx. 5500 individuals) ranked on basis of deprivation from 1 to 8414. This allows definition of ‘national’ quantiles.

Can be matched to ALSPAC via postcode data

Average KS2, by national quintiles of IMD

-0.19

0.06

0.09

0.21

0.43

0.02

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

Q1 (22.2%)

Q2 (17.5%)

Q3 (18.9%)

Q4 (16.9%)

Q5 (24.5%)


Average KS2 (std)

0.62

Subjective financial hardship

Measures: Mother-completed financial difficulties questionnaires at 8, 21, 33, 61 and 85 months

Format: ‘How difficult at the moment do you find to afford these items: food; clothing; heating; rent/mortgage; things for child?’

Very (3); Fairly (2); Slightly (1); Not difficult (0)Responses to the 5 items at each date summed to give to score between 0 and 15

The SEP index uses the mean score across the 5 datesThe 61 and 85 month measures include questions on educational courses, medical care, child care and other things‘Do not pay for this/DSS pays’ options for rent and heating coded as 0The distribution of the resulting variable in highly skewed

24

19

14

11

87

54

3 2 2 1 1 0 0 00

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mean financial difficulties score

% s

amp

le

Average KS2, by quintiles of financial difficulties score

-0.10

-0.01

0.16

0.27

0.39

-0.25

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Q1 (19.4%)

Q2 (19.4%)

Q3 (20.4%)

Q4 (21.0%)

Q5 (19.9%)


Average KS2 (std)

0.49100%

# SEP indicators missing (out of 10) Iterative multivariable regression technique – switching regression

Stata’s ice command

1. Specify a prediction equation for each variable

2. Randomly allocate values to missing cases

3. Predict values for missing cases

4. Update RHS variables and repeat cycle (10 times)

Options allow choice of estimation method, passive imputation and substitution of RHS dummies, constrained intervals for predicted values

# missing Obs % Cum. %0 3,887 29.0 29.01 2,746 20.5 49.52 2,277 17.0 66.53 1,679 12.5 79.04 755 5.6 84.75 827 6.2 90.86 488 3.6 94.57 403 3.0 97.58 337 2.5 100.0

Total 13,399 1009 1,110

Multiple Imputation by Chained Regression

Current method:Imputation carried out using 10 SEP variables only – does not use other informationOnly a single imputed dataset created

The ice command

ice $sesvars using sesimp.dta, replace cmd(mumed daded mumclass dadclass rawinc85:ologit, ownhouse: mlogit) passive (own_2:ownhouse==1 \ own_3: ownhouse==2 \ mumed_2:mumed==2 \ mumed_3:mumed==3 \ mumed_4:mumed==4 \ daded_2:daded==2 \ daded_3:daded==3 \ daded_4:daded==4 \ mclass_2: mumclass==2 \ mclass_3: mumclass==3 \ mclass_4: mumclass==4 \ mclass_5: mumclass==5 \ mclass_6: mumclass==6 \ dclass_2: dadclass==2 \ dclass_3: dadclass==3 \ dclass_4: dadclass==4 \ dclass_5: dadclass==5 \ dclass_6: dadclass==6 \ inc85_2: rawinc85==2 \ inc85_3: rawinc85==3 \ inc85_4: rawinc85==4 \ inc85_5: rawinc85==5 ) substitute (ownhouse:own_2 own_3, mumed:mumed_2 mumed_3 mumed_4, daded:daded_2 daded_3 daded_4, mumclass: mclass_2 mclass_3 mclass_4 mclass_5 mclass_6, dadclass:dclass_2 dclass_3 dclass_4 dclass_5 dclass_6, rawinc85:inc85_2 inc85_3 inc85_4 inc85_5) genmiss (miss_) seed(100);

Principal components analysis

PCA provides a way of combining (weighting) the individual components into a single index

PCA conducted on the 10x10 polychoric correlation matrixStandard PCA techniques assume continuous, normally distributed variables. Polychoric correlation can be used when there are binary and categorical components (e.g. education). It assumes that ordinal variables obtained by categorizing an normally distributed underlying variable.

PCA extracts a single component that maximises the explained proportion of the variation in the (standardised) components

Each component is assigned a scoring coefficient that is used as a weight in the construction of the SEP index

Principal components analysis

Scoring coefficients:

Preschool income 0.3556Age 7 income 0.3593Age 11 income 0.3307Mother's education 0.3272Partner's education 0.3365Mother's social class 0.2811Partner's social class 0.3033Ever social housing -0.3641Other housing 0.0350IMD rank at birth 0.2300Financial difficulties -0.2387

SEP index explains 46% of total variation in components

Average KS2, by quintiles of SEP index

-0.46

-0.10

0.12

0.38

0.73

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

Q1 (20.2%)

Q2 (21.1%)

Q3 (21.2%)

Q4 (20.2%)

Q5 (17.4%)

Average KS2 (std)

1.19

Summary

ALSPAC contains numerous indicators that can be used to construct an SEP index

Indicators vary in The type of resources they measure The sections of the population they distinguish (e.g. tenure appears

good at picking out the very disadvantaged, but does not discriminate at the top of the distribution)

The likelihood of non-response by different groups

Issues that need to be considered when constructing an index: Which components should be included? (Should education be

separate?) How should observations at multiple dates/by multiple respondents be

treated? How should missing values be dealt with? How should the components be combined?

Centre for Market and Public Organisation Measuring socio-economic position in ALSPAC Liz Washbrook,...

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