The Cox Model and Its Applications

Mikhail Nikulin

ISBN 10: 3662493314 / ISBN 13: 9783662493311

Published by Springer, Springer Gabler, 2016

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783662493311

Bibliographic Details

• Title: The Cox Model and Its Applications
• Publisher: Springer, Springer Gabler
• Publication Date: 2016
• Language: English
• ISBN 10: 3662493314
• ISBN 13: 9783662493311
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 8D millimeters 235 millimeters width by 155 millimeters height by 8 millimeters depth
• Weight: 224 grams

About this title

Synopsis

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.

About the Author

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.