Exploring the nature of covariate effects in the proportional hazards model.
We discuss an exploratory technique for investigating the nature of covariate effects in Cox's proportional hazards model. This technique features an additive term sigma p1 fj(chi ij), in place of the usual linear term sigma p1 chi ij beta j, where chi i1, chi i2,...,chi ip are covariate values for the ith individual. The fj(.) are unspecified smooth functions that are estimated using scatterplot smoothers. These functions can be used for descriptive purposes or to suggest transformations of the covariates. The estimation technique is a variation of the local scoring algorithm for generalized additive models (Hastie and Tibshirani, 1986, Statistical Science 1, 297-318).
Hastie
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Statistics and Data Analysis Research, AT&T Bell Laboratories, Murray Hill, New Jersey 07974.
Tibshirani
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R
D000465:Algorithms; D000704:Analysis of Variance; D000818:Animals; D004194:Disease / Q000209:etiology*; D006801:Humans; D009052:Leukemia Virus, Murine; D007942:Leukemia, Experimental / Q000235:genetics / Q000382:microbiology; D008433:Mathematics; D051379:Mice; D015233:Models, Statistical; D012307:Risk Factors