Probabilistic background.- Estimation for filtered counting process data.- Nonparametric procedures for survival data.- Additive Hazards Models.- Multiplicative hazards models.- Multiplicative-Additive hazards models.- Accelerated failure time and transformation models.- Clustered failure time data.- Competing Risks Model.- Marked point process models.

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.