The Cox Model and Its Applications, 1st ed. 2016 SpringerBriefs in Statistics Series

This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control.

Since Sir David Cox?s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data analysis.

Flexible semiparametric regression models are increasingly being used to relate lifetime distributions to time-dependent explanatory variables. Throughout the book, various recent statistical models are developed in close connection with specific data from experimental studies in clinical trials or from observational studies.

M.S. Nikulin received his Ph.D. at the V. Steklov Mathematical Institute in Moscow in (1973). He is a professor of statistics at the Bordeaux University since 1992. He is the author of 15 books and more than 200 papers.

Dr H.-D. I. Wu received his Ph.D. from the National Taiwan University and is currently an associate professor of statistics at the National Chung-Hsing University of Taiwan.

Offers a short-course or one-semester material for students, biostatisticians, and for scientific researchers who demand applications of survival analysis Illustrated with real life examples Demonstrates the application of the statistical methods to several datasets Includes supplementary material: sn.pub/extras