The book focuses on building concepts and procedure to perform Bayesian in Oncology setup. It presents the roles of Bayesian in Oncology to clinical medicine in the context of substantive and current applications. This book will help readers interested in exploring, understanding, and solving oncology research queries through Bayesian.
The book focuses on building concepts and procedure to perform Bayesian in Oncology setup. It presents the roles of Bayesian in Oncology to clinical medicine in the context of substantive and current applications. This book will help readers interested in exploring, understanding, and solving oncology research queries through Bayesian.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Atanu Bhattacharjee is an Assistant Professor at the Section of Biostatistics, Centre for Cancer Epidemiology, Tata Memorial Centre, India. He previously taught Biostatistics at the Malabar Cancer Centre, Kerala, India. He completed his PhD at Gauhati University, Assam, on Bayesian Statistical Inference. He is an elected member of the International Biometric Society (Indian Region). He served as Associate Editor of BMC Research Methodology. He has published over 200 research articles in various peer-reviewed journals.
Inhaltsangabe
Part 1 Bayesian in Clinical Research Chapter 1 Introduction to R and Open BUGS Chapter 2 Sample size determination Chapter 3 Study Design I Chapter 4 Study Design II Chapter 5 Optimum Biological Dose Selection Part 2 Bayesian in Time to Event Data Analysis Chapter 6 Survival Analysis Chapter 7 Competing Risk Data Analysis Chapter 8 Frailty Data Analysis Chapter 9 Relative Survival Analysis Part 3 Bayesian in Longitudinal Data Analysis Chapter 10 Longitudinal Data Analysis Chapter 11 Missing Data Analysis Chapter 12 Joint Longitudinal and Survival Analysis Chapter 13 Covariance modelling Part 4 Bayesian in Diagnostics Test Statistics Chapter 14 Bayesian Inference in Mixed Effect Model Chapter 15 Concordance Analysis Chapter 16 High Dimensional Data Analysis
Part 1 Bayesian in Clinical Research Chapter 1 Introduction to R and Open BUGS Chapter 2 Sample size determination Chapter 3 Study Design I Chapter 4 Study Design II Chapter 5 Optimum Biological Dose Selection Part 2 Bayesian in Time to Event Data Analysis Chapter 6 Survival Analysis Chapter 7 Competing Risk Data Analysis Chapter 8 Frailty Data Analysis Chapter 9 Relative Survival Analysis Part 3 Bayesian in Longitudinal Data Analysis Chapter 10 Longitudinal Data Analysis Chapter 11 Missing Data Analysis Chapter 12 Joint Longitudinal and Survival Analysis Chapter 13 Covariance modelling Part 4 Bayesian in Diagnostics Test Statistics Chapter 14 Bayesian Inference in Mixed Effect Model Chapter 15 Concordance Analysis Chapter 16 High Dimensional Data Analysis
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