Dynamic Regression Models for Survival Data

• Main Authors: Martinussen, Torben (Author), Scheike, Thomas H. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York, 2006.
• Series: Statistics for Biology and Health,
• Subjects: Statistics.; Statistics for Life Sciences, Medicine, Health Sciences.

In survival analysis there has long been a need for models that goes beyond the Cox model as the proportional hazards assumption often fails in practice. This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternat...

Table of Contents:

• 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.