Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research. Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censoring. It also describes techniques for modelling the occurrence of multiple events and event history analysis. Earlier chapters are now expanded to include new material on a number of topics, including measures of predictive ability and flexible para.;Chapter 1: Survival analysis -- Chapter 2: Some non-parametric procedures -- Chapter 3: The Cox regression model -- Chapter 4: Model checking in the Cox regression model -- Chapter 5: Parametric proportional hazards models -- Chapter 6: Accelerated failure time and other parametric models -- Chapter 7: Model checking in parametric models -- Chapter 8: Time-dependent variables -- Chapter 9: Interval-censored survival data -- Chapter 10: Frailty models -- Chapter 11: Non-proportional hazards and institutional comparisons -- Chapter 12: Competing risks -- Chapter 13: Multiple events and event history modelling -- Chapter 14: Dependent censoring -- Chapter 15: Sample size requirements for a survival study -- Appendix A: Maximum likelihood estimation -- Appendix B: Additional data sets -- Bibliography.