Random Effects Cox Models: A Poisson Modelling Approach

Renjun Ma (), Daniel Kerwski and Richard T. Burnett
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Renjun Ma: Faculty of Medicine, University of Ottawa
Daniel Kerwski: School of Mathematics and Statistics, Carleton University, and Faculty of Medicine, University of Ottawa
Richard T. Burnett: Faculty of Medicine, University of Ottawa, and Environmental Health Directorate, Health Canada

No lrsp-TRS338, RePAd Working Paper Series from Département des sciences administratives, UQO

Abstract: We propose a Poisson modelling approach to random effects Cox proportional hazards models. Specifically we describe methods of statistical inference for a class of random effects Cox models which accommodate a wide range of nested random effects distributions. The orthodox BLUP approach to random effects Poisson modeling techniques enables us to study this new class of models as a single class, rather than as a collection of unrelated models. The explicit expressions for the random effects given by our approach facilitate incorporation of relatively large number of random effects. An important feature of this approach is that the principal results depend only on the first and second moments of the unobserved random effects. The application of proposed methods is illustrated through the reanalysis of data on the time to failure (tumour onset) in an animal carcinogen esis experiment previously reported by Mantel and Ciminera (1979).

Keywords: Cox model; BLUP; estimating equation; frailty; generalized linear models; random effects; Tweedie exponential dispersion model (search for similar items in EconPapers)
JEL-codes: C10 C40 (search for similar items in EconPapers)
Date: Written 2000-02-01
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