Full Description
Through real-world case studies, this book shows how to use Stata to estimate a class of flexible parametric survival models. It discusses the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a particular disease when the cause of death has not been recorded. The book describes simple quantification of differences between any two covariate patterns through calculation of time-dependent hazard ratios, hazard differences, and survival differences.
Contents
Preface 1 Introduction 2 Using stset and stsplit 3 Graphical introduction to the principal datasets 4 Poisson models 5 Royston-Parmar models 6 Prognostic models 7 Time-dependent effects 8 Relative survival 9 Further topics
