Abstract:
:Analysis of panel data is often challenged by the presence of heterogeneity and state misclassification. In this paper, we propose a hidden mover-stayer model to facilitate heterogeneity for a population that consists of two subpopulations each of movers or of stayers and to simultaneously account for state misclassification. We develop an inference procedure based on the expectation-maximization algorithm by treating the mover-stayer indicator and underlying true states as latent variables. We evaluate the performance of the proposed method and investigate the impact of ignoring misclassification through simulation studies. The proposed method is applied to analyze the data arising from the Waterloo Smoking Prevention Project. Copyright © 2017 John Wiley & Sons, Ltd.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Yi GY,He W,He Fdoi
10.1002/sim.7346subject
Has Abstractpub_date
2017-09-10 00:00:00pages
3231-3243issue
20eissn
0277-6715issn
1097-0258journal_volume
36pub_type
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