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- Title
Robust estimation for panel count data with informative observation times and censoring times.
- Authors
Jiang, Hangjin; Su, Wen; Zhao, Xingqiu
- Abstract
We consider the semiparametric regression of panel count data occurring in longitudinal follow-up studies that concern occurrence rate of certain recurrent events. The analysis of panel count data involves two processes, i.e, a recurrent event process of interest and an observation process controlling observation times. However, the model assumptions of existing methods, such as independent censoring time and Poisson assumption, are restrictive and questionable. In this paper, we propose new joint models for panel count data by considering both informative observation times and censoring times. The asymptotic normality of the proposed estimators are established. Numerical results from simulation studies and a real data example show the advantage of the proposed method.
- Subjects
ASYMPTOTIC normality; CENSORING (Statistics); PANEL analysis; LONGITUDINAL method; COMPUTER simulation; RESEARCH; TIME; RESEARCH methodology; REGRESSION analysis; MEDICAL cooperation; EVALUATION research; DISEASE relapse; COMPARATIVE studies
- Publication
Lifetime Data Analysis, 2020, Vol 26, Issue 1, p65
- ISSN
1380-7870
- Publication type
journal article
- DOI
10.1007/s10985-018-09457-7