Weighting Your Data

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Weighting Your Data

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Weighting Your Data. General Information. Allows you to generalize your results to the entire population Necessary for all sampled based surveys Requirements Scientifically selected sample Complete documentation High overall response rate. What does weighting do?. It accounts for - PowerPoint PPT Presentation

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Page 1: Weighting Your Data

Weighting Your Data

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General Information

Allows you to generalize your results to the entire population

Necessary for all sampled based surveys Requirements

Scientifically selected sample Complete documentation High overall response rate

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What does weighting do?

It accounts for the probability of selection within the population non-response distribution of the target population by age and sex

It allows one participant to represent many others

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Probability of Selection from the Sample (Individual Weight)

Accounts for the variation in the selection probabilities in the sample

= 1/[(selection probability of cluster 1)* (selection probability of cluster 2)*(as many clusters until reach primary sampling unit)]

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Example

There are 12 districts and 3 are randomly selected; probability of selection at district level =.25

District Towns selected

Towns in district

Probability of selection (town)

INDIVIDUAL WEIGHT

A 8 30 .27 1/(.25*.27)

B 3 10 .30 1/(.25*.30)

C 5 22 .23 1/(.25*.23)

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Non-Response

Non-response can cause bias Information on response must be collected during

interviews Interview tracking form collects this information

Entered during data entry Automatically attached to dataset with Epi Info program

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Calculating the Non-Response Weight

Calculate non-response for each age and sex stratum

Non-response weight =

1/(response rate for age-sex stratum)

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Example

Males by age

Response Rate (RR)

Non-response weight = 1/RR

25–34 .94 1.064

35–44 .95 1.053

45–54 .87 1.149

55–64 .79 1.266

Non-response weights

would be calculated for

both men and women.

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Population Distribution

Used to adjust the sample to the target population "Post-stratification adjustments"

Need population information stratified by age and sex to calculate

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Calculating Population Weight

Population weight =

Proportion of population/Proportion of sample

Population weight =

(Age-Sex of population / Total population)

(Age-Sex of sample / Total Sample)

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Example

Males by age

Pop N Proportion of population (A)

Sample N Proportion of sample (B)

Weight

= A/B

25–34 2,000 .200 30 .075 2.667

35–44 1,760 .176 40 .100 1.760

45–54 1,440 .144 50 .125 1.152

55–64 1,600 .160 60 .150 1.067

Total 10,000 400

Post stratification would be calculated for males and females

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Overall Weight for Individual Steps

W1: Individual weight W2s1: Non-response weight W3: Population weight

WStep1= W1*W2s1*W3 WStep2= W1*W2s2*W3 WStep3= W1*W2s3*W3

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Weighting and STEPS

Tools to help calculate weights STEPSsampling.xls Interview_Tracking_Form.xls

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Weights

The Weights spreadsheet is used to document the sample selection and attach the weights to the dataset in Epi Info

Part of the spreadsheet is automated and parts need to be filled in by hand

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Weights: Example

Automatically entered

Enter by hand by matching information from PSU and Clustering SSU

Information available from Clustering SSU

spreadsheet Weighting Info

Information available from Rand Hhold

spreadsheet Weighting Info

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Attaching the Weights to Your Dataset

Once you have documented your weights using the STEPSsampling.xls Interviewtracking.xls

THEN …

You can use the generic analysis programs to automatically attach the weights to your dataset