Imputation of Missing Values When the Probability of Response Depends on the Variable Being Imputed
作者:
JohnS. Greenlees,
WilliamS. Reece,
KimberlyD. Zieschang,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1982)
卷期:
Volume 77,
issue 378
页码: 251-261
ISSN:0162-1459
年代: 1982
DOI:10.1080/01621459.1982.10477793
出版商: Taylor & Francis Group
关键词: Nonresponse;Imputation;Prediction approach;Censoring;Current Population Survey
数据来源: Taylor
摘要:
A method is developed for imputing missing values when the probability of response depends upon the variable being imputed. The missing data problem is viewed as one of parameter estimation in a regression model with stochastic censoring of the dependent variable. The prediction approach to imputation is used to solve this estimation problem. Wages and salaries are imputed to non-respondents in the Current Population Survey and the results are compared to the nonrespondents' IRS wage and salary data. The stochastic censoring approach gives improved results relative to a prediction approach that ignores the response mechanism.
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