Incorporating complex sample design effects when only final survey weights are available
Brady T. West
Survey Research Center
Institute for Social Research
University of Michigan, Ann Arbor
Ann Arbor, MI
[email protected]
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Sean Esteban McCabe
Institute for Research on Women and Gender
Substance Abuse Research Center
University of Michigan, Ann Arbor
Ann Arbor, MI
[email protected]
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Abstract. In this article, we consider the situation that arises when a survey
data producer has collected data from a sample with a complex design (possibly
featuring stratification of the population, cluster sampling, and unequal probabilities
of selection) and for various reasons only provides secondary analysts of
those survey data with a final survey weight for each respondent and “average”
design effects for survey estimates computed from the data. In general, these “average”
design effects, presumably computed by the data producer in a way that
fully accounts for all the complex sampling features, already incorporate possible
increases in sampling variance due to the use of the survey weights in estimation.
The secondary analyst of the survey data—who uses the provided information
to compute weighted estimates; computes design-based standard errors reflecting
variance in the weights (by using Taylor series linearization, for example); and
inflates the estimated variances using the “average” design effects
provided—is
applying a “double” adjustment to the standard errors for the effect of weighting
on the variance estimates, leading to overly conservative inferences. We propose a
simple method to prevent this problem and provide a Stata program for applying
appropriate adjustments to variance estimates in this situation. We illustrate two
applications of the method with survey data from the Monitoring the Future study
and conclude with suggested directions for future research in this area.
View all articles by these authors:
Brady T. West, Sean Esteban McCabe
View all articles with these keywords:
deft2corr, survey design effects, survey weights, average design effects
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