The demonstration of varying treatment effects among different subjects of patients is an important part of the analysis of clinical trials. But issues of censoring, truncation and inclusion criteria complicate the analysis of clinical trial data. Recent advances in proportional hazard methodologies provide regression diagnostics, improved point and interval estimates of the parameters of survival functions, handling of time dependent covariates in the analysis. This paper discusses the interactions between treatment and patient in the presence of censoring and to account heterogeneity using frailty model. The application of the frailty model with respect to pulmonary tuberculosis data are presented and discussed.
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