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Semiparametric maximum likelihood inference by using failed contact attempts to adjust for nonignorable nonresponse

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  • Jing Qin
  • Dean A. Follmann

Abstract

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 nonignorable, 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.

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  • Jing Qin & Dean A. Follmann, 2014. "Semiparametric maximum likelihood inference by using failed contact attempts to adjust for nonignorable nonresponse," Biometrika, Biometrika Trust, vol. 101(4), pages 985-991.
    • Handle: RePEc:oup:biomet:v:101:y:2014:i:4:p:985-991.
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    File URL: http://hdl.handle.net/10.1093/biomet/asu046
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    Cited by:

    1. Heng Chen & Geoffrey Dunbar & Q. Rallye Shen, 2020. "The Mode is the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 341-357, Emerald Group Publishing Limited.

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