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The Stata Journal
Volume 9 Number 2: pp. 265-290



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Further development of flexible parametric models for survival analysis

Paul C. Lambert
Centre for Biostatistics and Genetic
Epidemiology
Department of Health Sciences
University of Leicester, smrm
UK
paul.lambert@le.ac.uk
Patrick Royston
Clinical Trials Unit
Medical Research Council
London,
UK
patrick.royston@ctu.mrc.ac.uk
Abstract.  Royston and Parmar (2002, Statistics in Medicine 21: 2175–2197) developed a class of flexible parametric survival models that were programmed in Stata with the stpm command (Royston, 2001, Stata Journal 1: 1–28). In this article, we introduce a new command, stpm2, that extends the methodology. New features for stpm2 include improvement in the way time-dependent covariates are modeled, with these effects far less likely to be over parameterized; the ability to incorporate expected mortality and thus fit relative survival models; and a superior predict command that enables simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences. The ideas are illustrated through a study of breast cancer survival and incidence of hip fracture in prostate cancer patients.
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