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Bayesian Latent Pattern Mixture Models for Handling Attrition in Panel Studies With Refreshment Samples

Authors
  • Si, Yajuan
  • Reiter, Jerome P.
  • Hillygus, D. Sunshine
Type
Preprint
Publication Date
Sep 07, 2015
Submission Date
Sep 07, 2015
Identifiers
arXiv ID: 1509.02124
Source
arXiv
License
Yellow
External links

Abstract

Many panel studies collect refreshment samples---new, randomly sampled respondents who complete the questionnaire at the same time as a subsequent wave of the panel. With appropriate modeling, these samples can be leveraged to correct inferences for biases caused by non-ignorable attrition. We present such a model when the panel includes many categorical survey variables. The model relies on a Bayesian latent pattern mixture model, in which an indicator for attrition and the survey variables are modeled jointly via a latent class model. We allow the multinomial probabilities within classes to depend on the attrition indicator, which offers additional flexibility over standard applications of latent class models. We present results of simulation studies that illustrate the benefits of this flexibility. We apply the model to correct attrition bias in an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

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