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Published on: October 23, 2020
A flexible semiparametric transformation model for survival data
1Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5 B, 2099, Copenhagen K, Denmark. ts@pubhealth.ku.dk
Abstract:
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.
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