Seminar at SMU Delhi
March 7, 2013 (Thursday) ,
2:15 PM at Webinar
Indian Statistical Institute, Chennai
Additive hazards models for gap time data with multiple causes
Abstract of Talk
Recurrent event data with multiple causes are often observed in biomedical studies. The
additive hazards model describes a different aspect of the association between covariates
and the failure time than does the proportional hazards model. Here, we introduce additive
hazards models for the analysis of gap time data of recurrent events with multiple causes.
We estimate the regression parameter vector and cumulative baseline cause specific hazard
rate function using counting process approach. Asymptotic properties of the estimators are
studied. The proposed model is applied to a real data set. A simulation study is carried out to
assess the performance of the estimates.