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| Royston, Patrick. |
| Since its introduction to a wondering public in 1972, the Cox proportional hazards regression model has become an overwhelmingly popular tool in the analysis of censored survival data. However, some features of the Cox model may cause problems for the analyst or an interpreter of the data. They include the restrictive assumption of proportional hazards for covariate effects, and “loss” (non-estimation) of the baseline hazard function induced by conditioning on event times. In medicine, the hazard function is often of fundamental interest since it represents an important aspect of the time course of the disease in question. In the present article, the Stata implementation of a class of flexible parametric survival models recently proposed by Royston and... |
| Tipo: Journal Article |
Palavras-chave: Parametric survival analysis; Hazard function; Proportional hazards; Proportional odds; Research Methods/ Statistical Methods. |
| Ano: 2001 |
URL: http://purl.umn.edu/115931 |
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