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Penalized likelihood in Cox regression
Author(s) -
Verweij Pierre J. M.,
Van Houwelingen Hans C.
Publication year - 1994
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780132307
Subject(s) - proportional hazards model , statistics , regression , regression analysis , mathematics , likelihood function , regression function , econometrics , maximum likelihood
In a Cox regression model, instability of the estimated regression coefficients can be reduced by maximizing a penalized partial log‐likelihood, where a penalty function of the regression coefficients is substracted from the partial log‐likelihood. In this paper, we choose the optimal weight of the penalty function by maximizing the predictive value of the model, as measured by the crossvalidated partial log‐likelihood. Our methods are illustrated by a study of ovarian cancer survival and by a study of centre effects in kidney graft survival.