Not Asked and Not Answered: Multiple Imputation for Multiple Surveys

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Not Asked and Not Answered: Multiple Imputation for Multiple Surveys

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Title: Not Asked and Not Answered: Multiple Imputation for Multiple Surveys
Author: King, Gary; Gelman, Andrew; Liu, Chuanhai

Note: Order does not necessarily reflect citation order of authors.

Citation: Gelman, Andrew, Gary King and Chuanhai Liu. 1999. Not asked and not answered: multiple imputation for multiple surveys. Journal of the American Statistical Association 93(443): 846-857.
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Abstract: We present a method of analyzing a series of independent cross-sectional surveys in which some questions are not answered in some surveys and some respondents do not answer some of the questions posed. The method is also applicable to a single survey in which different questions are asked or different sampling methods are used in different strata or clusters. Our method involves multiply imputing the missing items and questions by adding existing methods of imputation designed for single surveys a hierarchical regression that allows co variates at the individual and survey levels. Information from survey weights is exploited by including in the analysis the variables on which the weights are based, and then reweighting individual responses (observed and imputed) to estimate population quantities. We also develop diagnostics for checking the fit of the imputation model based on comparing imputed data to nonimputed data. We illustrate with the example that motivated this project: a study of pre-election public opinion polls in which not all the questions of interest are asked in all the surveys, so that it is infeasible to impute with in each survey separately.
Published Version: doi:10.2307/2669819
Other Sources: http://gking.harvard.edu/files/not.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4266394

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  • FAS Scholarly Articles [6929]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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