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Survey Weights: An Example from Honduras. Bob Gerzoff U.S. Centers for Disease Control and Prevention. 8 th CAMDI Workshop, Panamá City, 28–29 November 2006. Outline. Why weight? Steps to calculating weights. Sample calculation from Honduras. Why Weight?.
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Survey Weights:An Example from Honduras Bob Gerzoff U.S. Centers for Disease Control and Prevention 8th CAMDI Workshop, Panamá City, 28–29 November 2006
Outline • Why weight? • Steps to calculating weights. • Sample calculation from Honduras
Why Weight? • Simple averages assume everyone has the same chance of being selected for the survey. • Need to correct for unequal probability of selection. • Unequal selection probability impacts both the means and their confidence intervals
Why Weight(2)? • Need to correct for non–response. • Want to adjust results to reflect the larger population from which the sample was taken
Steps to Calculating Weights • Calculate a “sampling weight” • Adjust the sampling weight for non–response
Calculating the Sampling Weight • Sampling weights are the inverse (reciprocal) of the probability of selection. • Sampling weights are calculated for each level of sampling. • Sampling weights for each level are multiplied together
Sampling Weights in the Honduran Sample • Four of 20 sectors were chosen. • The probability of selection is 4/20. • The sampling weight for the sector level (for all sectors) is 20/4=5. • This weight applies to all individuals the sector.
Sampling Weights in the Honduran Sample • In sector 2, there are ~17 compactos (blocks). • The probability of selecting any compacto is 3/17. • The sampling weight for the compacto level (for all compactos in sector 2 ) is 17/3 • This weight applies to all individuals in this compacto.
Sampling Weights in the Honduran Sample • The sampling weight for all 144 individuals in sector 2 is: 5 * 17/3 = 28.3
Sampling Weights in the Honduran Sample • The intent was to sample all households and all adults within each chosen sector/compacto. • The probability of selection at both those levels is therefore 1.
Adjusting the Weights for Non-Response • Although the intent was to sample every household and all adults, not every or every adult was sampled. • Need to adjust the weights for non-response at the household and individual level.
Adjusting the Weights for Household Non-Response • In sector 2, compacto 11, there were 70 households: 50 were sampled. • Each household should therefore represent 70/50 or 1.4 households.
Adjusting the Weights for Individual Level Non-Response • Adjustments to the sampling weights for individual level non–response are made specific for each age and sex combination.
Adjusting the Weights for Individual Level Non-Response • In sector 2, compacto 11, there were 43 females age 20-39 to survey: 20 were surveyed. • Therefore, each female age 20-39 in sector 2, compacto 11 represents approximately 43/20 (2.5) individuals.
Adjusting the Weights for Individual Level Non–Response • In sector 2, compacto 11, there were 4 males 65 or older to survey: Three were surveyed. • Therefore, each male 65 or older in sector 2, compacto 11 represents approximately 4/3 (1.3) individuals.
Adjusting the Weights for Individual Level Non-Response • For a male, 65 or older, in sector 2, compacto 2 the sampling weight becomes: 28.3*1.3=36.8 • For a female, age 20-39 in sector 2, compacto 2, the sampling weight becomes: 28.3*2.5=70.8
Scale the Weights • When all the weights have been calculated, they are scaled to represent the target population.
Scale the Weights • If this is done to maintain the population subcategory relative sizes it is called, Raking.
Standardization • The age/sex distribution of the sample may not be the same as the target population. • Raked weights automatically “correct” for this problem
Standardization • If the age/sex distribution of the sample does not differ markedly from the sample, then we may decide not to standardize. • We may, however, decide to standardize so that our estimates reflect the larger target population.