Statistical Methods for Survival Data Analysis, 4th Edition

Praise for the Third Edition

". . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject." --Statistics in Medical Research

Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences.

Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes:
* Marginal and random effect models for analyzing correlated censored or uncensored data
* Multiple types of two-sample and K-sample comparison analysis
* Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models
* Expanded coverage of the Cox proportional hazards model
* Exercises at the end of each chapter to deepen knowledge of the presented material

Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.

Statistical methods for survival data analysis continues to flourish in modern research, with applications expanding from their historical use in cancer and reliability research to the areas of business, epidemiology, and the social and behavioral sciences. Statistical Methods for Survival Data Analysis, Fourth Editionprovides a comprehensive introduction to the most commonly-used methods for analyzing survival data. The book begins with basic definitions and interpretations of survival functions and goes on to guide readers through parametric and nonparametric methods for estimating and comparing these functions and the search for a theoretical distribution to fit the data. Also discussed are the parametric and nonparametric approaches to the identification of prognostic factors that are related to survival as well as the regression methods for identifying risk factors for dichotomous and polychotomous outcomes. The Fourth Edition continues to provide an application-oriented approach, with a minimum level of mathematics. The new edition now features coverage of marginal models and random effect models for analyzing correlated censored or uncensored data;  a completely updated chapter on goodness of fit and revised treatment of parametric methods for regression model fitting that now includes a focus on accelerated failure time models; expanded discussion on the Cox proportional hazards model. A large number of practical examples are given that utilize SAS, SPSS, and R software to assist readers with understanding the methods and in interpreting the results.

Praise for the Third Edition . . . an easy-to read introduction to survival analysis which covers the major concepts and techniques of the subject. --Statistics in Medical Research Updated and expanded to reflect the latest developments, Statistical Methods for Survival Data Analysis, Fourth Edition continues to deliver a comprehensive introduction to the most commonly-used methods for analyzing survival data. Authored by a uniquely well-qualified author team, the Fourth Edition is a critically acclaimed guide to statistical methods with applications in clinical trials, epidemiology, areas of business, and the social sciences. The book features many real-world examples to illustrate applications within these various fields, although special consideration is given to the study of survival data in biomedical sciences. Emphasizing the latest research and providing the most up-to-date information regarding software applications in the field, Statistical Methods for Survival Data Analysis, Fourth Edition also includes: Marginal and random effect models for analyzing correlated censored or uncensored data Multiple types of two-sample and K-sample comparison analysis Updated treatment of parametric methods for regression model fitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of the presented material Statistical Methods for Survival Data Analysis is an ideal text for upper-undergraduate and graduate-level courses on survival data analysis. The book is also an excellent resource for biomedical investigators, statisticians, and epidemiologists, as well as researchers in every field in which the analysis of survival data plays a role.