title: SEMIPARAMETRIC TRANSFORMATION MODELS WITH RANDOM EFFECTS FOR CLUSTERED FAILURE TIME DATA.
abstract: We propose a general class of semiparametric transformation models with random effects to formulate the effects of possibly time-dependent covariates on clustered or correlated failure times. This class encompasses all commonly used transformation models, including proportional hazards and proportional odds models, and it accommodates a variety of random-effects distributions, particularly Gaussian distributions. We show that the nonparametric maximum likelihood estimators of the model parameters are consistent, asymptotically normal and asymptotically efficient. We develop the corresponding likelihood-based inference procedures. Simulation studies demonstrate that the proposed methods perform well in practical situations. An illustration with a well-known diabetic retinopathy study is provided.
authors.affiliation: Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599-7420, U.S.A. E-mail: dzeng@bios.unc.edu.
authors.forename: Donglin
authors.initials: D
authors.lastname: Zeng
authors.forename: D Y
authors.initials: DY
authors.lastname: Lin
authors.forename: Xihong
authors.initials: X
authors.lastname: Lin