Marginal Regression of Gaps Between Recurrent Events

Authors: Huang Y.¹; Chen Y.Q.²

Source: Lifetime Data Analysis, Volume 9, Number 3, September 2003 , pp. 293-303(11)

Publisher: Springer

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Abstract:

Recurrent event data typically exhibit the phenomenon of intra-individual correlation, owing to not only observed covariates but also random effects. In many applications, the population may be reasonably postulated as a heterogeneous mixture of individual renewal processes, and the inference of interest is the effect of individual-level covariates. In this article, we suggest and investigate a marginal proportional hazards model for gaps between recurrent events. A connection is established between observed gap times and clustered survival data with informative cluster size. We subsequently construct a novel and general inference procedure for the latter, based on a functional formulation of standard Cox regression. Large-sample theory is established for the proposed estimators. Numerical studies demonstrate that the procedure performs well with practical sample sizes. Application to the well-known bladder tumor data is given as an illustration.

Keywords: clustered survival data; estimating equation; partial score; proportional hazards model; renewal process; semiparametric inference

Language: English

Document Type: Research article

Affiliations: 1: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA eugene@fhcrc.org 2: Program in Biostatistics, School of Public Health, University of California, Berkeley, CA yqchen@stat.berkeley.edu

Publication date: 2003-09-01