Extensions and applications of the Cox-Aalen survival model. Biometrics 2003 Dec;59(4):1036-45
Date
02/19/2004Pubmed ID
14969483DOI
10.1111/j.0006-341x.2003.00119.xScopus ID
2-s2.0-0346102883 (requires institutional sign-in at Scopus site) 70 CitationsAbstract
Cox's regression model is the standard regression tool for survival analysis in most applications. Often, however, the model only provides a rough summary of the effect of some covariates. Therefore, if the aim is to give a detailed description of covariate effects and to consequently calculate predicted probabilities, more flexible models are needed. In another article, Scheike and Zhang (2002, Scandinavian Journal of Statistics 29, 75-88), we suggested a flexible extension of Cox's regression model, which aimed at extending the Cox model only for those covariates where additional flexibility are needed. One important advantage of the suggested approach is that even though covariates are allowed a nonparametric effect, the hassle and difficulty of finding smoothing parameters are not needed. We show how the extended model also leads to simple formulae for predicted probabilities and their standard errors, for example, in the competing risk framework.
Author List
Scheike TH, Zhang MJAuthor
Mei-Jie Zhang PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
BiometryConfidence Intervals
Humans
Melanoma
Myocardial Infarction
Probability
Proportional Hazards Models
Survival Analysis
Time Factors
