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Semiparametric analysis of longitudinal data with informative observation times and censoring times

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  • Wen Su
  • Hangjin Jiang

Abstract

We focus on regression analysis of irregularly observed longitudinal data which often occur in medical follow-up studies and observational investigations. The model for such data involves two processes: a longitudinal response process of interest and an observation process controlling observation times. Restrictive models and questionable assumptions, such as Poisson assumption and independent censoring time assumption, were posed in previous works for analysing longitudinal data. In this paper, we propose a more general model together with a robust estimation approach for longitudinal data with informative observation times and censoring times, and the asymptotic normalities of the proposed estimators are established. Both simulation studies and real data application indicate that the proposed method is promising.

Suggested Citation

  • Wen Su & Hangjin Jiang, 2018. "Semiparametric analysis of longitudinal data with informative observation times and censoring times," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(11), pages 1978-1993, August.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:11:p:1978-1993
    DOI: 10.1080/02664763.2017.1403574
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