Semiparametric maximum likelihood inference by using failed contact attempts to adjust for nonignorable nonresponse
成果类型：
Article
署名作者：
Qin, Jing; Follmann, Dean A.
署名单位：
National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asu046
发表日期：
2014
页码：
985991
关键词：
摘要：
In marketing research, social science and epidemiological studies, call-back of nonrespondents is standard. If respondents and nonrespondents tend to give different answers, the missing data are called non-ignorable, and using them alone may produce biased results. To extend earlier work on nonresponse in the presence of call-backs, Alho (1990) proposed modelling the probability of response at each attempt through logistic regression, where outcomes of interest and covariates are explanatory variables. In this paper we propose a semiparametric maximum likelihood approach, and discuss large-sample properties and the semiparametric likelihood ratio statistic used to test whether the data are missing completely at random. Simulations are conducted to evaluate this approach and a modification of the method of Alho (1990). Data from the National Health Interview Survey are used for illustration.