Advanced Survival Models

Survival data analysis is a broad field of statistics used in medical research, with several extensions of classical survival models developed to address particular situations. This book aims to gather the most commonly used extensions, such as frailty models, cure models, competing risk models, and joint survival models, and provides an introduction to the understanding, implementation, and interpretation of these models for applied statisticians and graduate students.

Format: Paperback / softback
Length: 334 pages
Publication date: 26 September 2022
Publisher: Taylor & Francis Ltd

Survival data analysis is a vast and intricate domain within the realm of statistics, encompassing a diverse array of methodologies employed across a wide spectrum of applications, particularly in the field of medical research. Over the past two decades, significant advancements have been made in developing specialized survival models to address specific scenarios frequently encountered in practical settings. The primary objective of this book is to compile the most commonly utilized extensions of classical survival models into a single comprehensive resource. These extensions include frailty models, which account for unobserved heterogeneity or clustered data; cure models, which account for the non-occurrence of an event among a fraction of the population; competing risk models, which account for the occurrence of multiple events; and joint survival models, which simultaneously analyze a time-to-event endpoint and a longitudinal outcome.

The book adopts a consistent notation throughout, ensuring clarity and uniformity in the presentation of the various techniques. It elucidates the appropriate application of each survival model based on the specific research questions at hand and elucidates the connections between these models and the underlying research objectives. The text strikes a balance between providing a thorough methodological development suitable for advanced graduate students and applied statisticians, while also offering an accessible introduction for methodological researchers interested in exploring the major extensions of classical survival analysis.

This book is primarily designed to cater to applied statisticians and graduate students specializing in statistics and biostatistics. It can also serve as a valuable reference for methodological researchers seeking to delve into the core advancements of survival analysis. By consolidating the most widely employed extensions within a single volume, this book aims to facilitate a deeper understanding of survival data analysis and its practical applications, empowering researchers to make informed decisions based on robust statistical methodologies.

Weight: 558g
Dimension: 156 x 235 x 26 (mm)
ISBN-13: 9780367715366