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Regression analysis of panel count data with covariate-dependent observation and censoring times

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Panel count data often occur in a long-term study where the primary end point is the time to a specific event and each subject may experience multiple recurrences of this event. Furthermore, suppose that it is not feasible to keep subjects under observation continuously and the numbers of recurrences for each subject are only recorded at several distinct time points over the study period. Moreover, the set of observation times may vary from subject to subject. In this paper, regression methods, which are derived under simple semiparametric models, are proposed for the analysis of such longitudinal count data. Especially, we consider the situation when both observation and censoring times may depend on covariates. The new procedures are illustrated with data from a well-known cancer study.
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Keywords: Counting process; Cox model; Estimating function; Recurrent events

Document Type: Research Article

Affiliations: 1: University of Missouri, Columbia, USA 2: Harvard University, Boston, USA

Publication date: February 1, 2000

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