The Cox proportional hazards (PH) model usually assumes linearity of the covariates on the log hazard function, which may be violated because linearity cannot always be guaranteed. We propose a partially linear single-index proportional hazards regression model, which can model both linear and nonlinear covariate effects on the log hazard in the proportional hazards model. We adopt a polynomial...

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.

ABSTRACT Survival analysis involves the modeling of time-to-event data whereby death or failure is considered an "event". The graphic presentation of Cox proportional hazards model using SAS PHREG is a significant tool which facilitates effective data exploration in survival analysis. The SAS PROC PHREG can generate some of the useful survival analysis plots using the ODS graphics option in ver...

In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the Cox regression method, and to provide some guidance regarding the presentation of the results. Cop...