Functional form diagnostics for Cox's proportional hazards model.

Sheppard's correction for grouping in Cox's proportional hazards model

Cox's proportional hazards model is often t to grouped survival data, i.e. occurrence/exposure data over given time intervals and covariate strata. We derive a Sheppard correction for the bias in the grouped data analogue of Cox's maximum partial likelihood estimator. This is done via a large sample theory in which the covariate strata and time intervals shrink as the sample size increases.

Variable Selection for Cox's Proportional Hazards Model and Frailty Model

Fitting Cox's Proportional Hazards Model Using Grouped Survival Data

Cox's proportional hazard model is often t to grouped survival data (i.e., occurrence and exposure data over various speci ed time-intervals and covariate bins), as opposed to continuous data. The practical limits to using such data for inference in the Cox model are investigated. A large sample theory, allowing the bins and time-intervals to shrink as the sample size increase, is developed. It...

Influence Diagnostics for the Proportional Hazards Model

Influence diagnostics based on Cook’s curvature diagnostic (1986) are developed for the proportional hazards model. Three perturbation schemes are considered: perturbation of the likelihood, perturbation of the censoring information and perturbation of covariate values.

SUGI 28: Let the Data Speak: New Regression Diagnostics Based on Cumulative Residuals

Residuals have long been used as the basis for graphical and numerical examination of the adequacy of regression models. Conventional residual analysis based on plotting raw residuals or their smoothed versions is highly subjective, whereas most goodness-offit tests provide little information about the nature of model inadequacy. In this paper, new model-checking techniques of Lin et al. (1993,...