Hierarchical logistic regression models for imputation of unresolved enumeration status in undercount estimation.
"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."
Belin
T R
TR
Diffendal
G J
GJ
Mack
S
S
Rubin
D B
DB
Schafer
J L
JL
Zaslavsky
A M
AM
D000569:Americas; D019352:Censuses; D003625:Data Collection; D019049:Developed Countries; D016015:Logistic Models; D008962:Models, Theoretical; D009656:North America; D011154:Population Characteristics; D011336:Probability; D012106:Research; D012107:Research Design; D012494:Sampling Studies; D013223:Statistics as Topic; D014481:United States
Americas; Census; Census Methods; Data Adjustment; Developed Countries; Error Sources; Estimation Technics; Logistic Model; Mathematical Model; Measurement; Models, Theoretical; Nonrespondents; North America; Northern America; Population Statistics; Probability; Research Methodology; Sampling Studies; Statistical Studies; Studies; Surveys; Undercount; United States