Additive transformation models for clustered failu

Authors: Donglin Zeng Jianwen Cai

Publish Date: 2009/12/11

Volume: 16, Issue: 3, Pages: 333-352

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Abstract

We propose a class of additive transformation risk models for clustered failure time data Our models are motivated by the usual additive risk model for independent failure times incorporating a frailty with mean one and constant variability which is a natural generalization of the additive risk model from univariate failure time to multivariate failure time An estimating equation approach based on the marginal hazards function is proposed Under the assumption that cluster sizes are completely random we show the resulting estimators of the regression coefficients are consistent and asymptotically normal We also provide goodnessoffit test statistics for choosing the transformation Simulation studies and real data analysis are conducted to examine the finitesample performance of our estimators

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