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Analysis of binary longitudinal data with time-varying effects

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  • Jeong, Seonghyun
  • Park, Minjae
  • Park, Taeyoung

Abstract

This paper considers the analysis of longitudinal data where a binary response variable is observed repeatedly for each subject over time. In analyzing such data, regression coefficients are commonly assumed constant over time, which may not properly account for the time-varying effects of some subject characteristics on a sequence of binary outcomes. This paper proposes a Bayesian method for the analysis of binary longitudinal data with time-varying regression coefficients and random effects to account for nonlinear subject-specific effects over time as well as between-subject variation. The proposed method facilitates posterior computation via the method of partial collapse and accommodates spatially inhomogeneous smoothness of nonparametric functions without overfitting via a basis search technique. The proposed method is illustrated with a simulated study and the binary longitudinal data from the German socioeconomic panel study.

Suggested Citation

  • Jeong, Seonghyun & Park, Minjae & Park, Taeyoung, 2017. "Analysis of binary longitudinal data with time-varying effects," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 145-153.
    • Handle: RePEc:eee:csdana:v:112:y:2017:i:c:p:145-153
    DOI: 10.1016/j.csda.2017.03.007
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    References listed on IDEAS

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    2. Hao Cheng, 2023. "Quantile varying-coefficient structural equation model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(5), pages 1439-1475, December.

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