Cure Models

Methods, Applications, and Implementation
1. Auflage 2021
ISBN: 978-0-367-14557-6
Verlag: CRC Press

Buch, Englisch, 268 Seiten, Format (B × H): 158 mm x 237 mm, Gewicht: 536 g

Reihe: Chapman & Hall/CRC Biostatistics Series

Cure Models: Methods, Applications and Implementation is the first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models, including estimation, inference, and software. This book is useful for statistical researchers and graduate students, and practitioners in other disciplines to have a thorough review of modern cure model methodology and to seek appropriate cure models in applications. The prerequisites of this book include some basic knowledge of statistical modeling, survival models, and R and SAS for data analysis.

The book features real-world examples from clinical trials and population-based studies and a detailed introduction to R packages, SAS macros, and WinBUGS programs to fit some cure models. The main topics covered include

- the foundation of statistical estimation and inference of cure models for independent and right-censored survival data,

- cure modeling for multivariate, recurrent-event, and competing-risks survival data, and joint modeling with longitudinal data,

- statistical testing for the existence and difference of cure rates and sufficient follow-up,

- new developments in Bayesian cure models,

- applications of cure models in public health research and clinical trials.

Autoren/Hrsg.

Peng, Yingwei

Yu, Binbing

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik

Inhaltsverzeichnis

1. Introduction. 2. The Parametric Cure Model. 3. The Semiparametric and Nonparametric Cure Models. 4. Cure Models for Multivariate Survival Data and Competing Risks. 5. Joint Modeling of Longitudinal and Survival Data with a Cure Fraction. 6. Testing the Existence of Cured Subjects and Sufficient Follow-up. 7. Bayesian Cure Model. 8. Analysis of Population-Based Cancer Survival Data. 9. Design and Analysis of Cancer Clinical Trials.

Über Autor(innen)

Yingwei Peng is Professor of Biostatistics in the Departments of Public Health Sciences and Mathematics and Statistics at Queen’s University and a senior Biostatistician at Queen’s Cancer Research Institute. He has been an Associate Editor of Canadian Journal of Statistics since 2010 and provided referee services to all mainstream statistical journals and Canadian federal funding agencies (NSERC and CIHR). He offered short courses on cure models, either by himself or with Jeremy Taylor (University of Michigan, USA), in Joint Statistical Meetings, ENAR Spring Meeting, and Université catholique de Louvain, Belgium, in 2014. Binbing Yu is an Associate Director in the AstraZeneca oncology biometric group. He has extensive experience in the applications of cure models in public health, clinical trials and health economics and made notable contributions to the development and enhancement of cure modeling for the presentation and analysis of cancer survival data for the USA National Cancer Institute.