Hierarchical logistic regression models for imputation of unresolved enumeration status in undercount estimation
Belin, T.R.; Diffendal, G.J.; Mack, S.; Rubin, D.B.; Schafer, J.L.; Zaslavsky, A.M.
Journal of the American Statistical Association 88(423): 1,149-1,166
1993
ISSN/ISBN: 0162-1459 PMID: 12155420 DOI: 10.2307/2290812Document Number: 324911
"In this article we describe a logistic regression modeling approach for nonresponse in the [U.S.] Post-Enumeration Survey (PES) that has desirable theoretical properties and that has performed well in practice.... In the 1990 PES, interviews were not obtained from approximately 1.2% of households in the sample, and approximately 2.1% of the individuals in interviewed households were considered unresolved after follow-up....The missing binary enumeration statuses for these unresolved cases were replaced with probabilities estimated under a statistical model that incorporated covariate information observed for these cases. This article describes an approach to modeling missing binary outcomes when there are a large number of covariates."