A flexible semiparametric transformation model for survival data.
I suggest an extension of the semiparametric transformation model that specifies a time-varying regression structure for the transformation, and thus allows time-varying structure in the data. Special cases include a stratified version of the usual semiparametric transformation model. The model can be thought of as specifying a first order Taylor expansion of a completely flexible baseline. Large sample properties are derived and estimators of the asymptotic variances of the regression coefficients are given. The method is illustrated by a worked example and a small simulation study. A goodness of fit procedure for testing if the regression effects lead to a satisfactory fit is also suggested.
Scheike
Thomas H
TH
Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5 B, 2099, Copenhagen K, Denmark. ts@pubhealth.ku.dk
D001699:Biometry; D016001:Confidence Intervals; D006801:Humans; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000401:mortality; D016017:Odds Ratio; D016016:Proportional Hazards Models; D016019:Survival Analysis