Estimating Heterogeneity in the Probabilities of Enumeration for Dual-System Estimation
作者:
JuhaM. Alho,
MaryH. Mulry,
Kent Wurdeman,
Jay Kim,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1993)
卷期:
Volume 88,
issue 423
页码: 1130-1136
ISSN:0162-1459
年代: 1993
DOI:10.1080/01621459.1993.10476386
出版商: Taylor & Francis Group
关键词: Capture-recapture;Correlation bias;Logistic regression;Nonsampling error;Post-Enumeration Survey
数据来源: Taylor
摘要:
We show how conditional logistic regression can be used to estimate the probability of being enumerated in a census and apply the model to the 1990 Post-Enumeration Survey (PES) in the United States. The estimates can be used in the estimation of population size and the estimation of correlation bias, for example. Unlike the classical stratification approach, the logistic approach permits the use of continuous explanatory variables. Model choice can be based on the standard techniques of the generalized linear models. We discuss some special problems caused by the fact that the PES sample area is open to migration between the captures. We also consider the effect of data errors in estimation. We characterize hard-to-enumerate populations and give some tentative estimates of correlation bias.
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