The Cox Model and Its Applications

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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 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. Topics Statistical Theory and Methods Statistics for Life Sciences, Medicine, Health Sciences Biostatistics Epidemiology

Author(s): Mikhail Nikulin, Hong-Dar Isaac Wu
Series: SpringerBriefs in Statistics
Edition: 1
Publisher: Springer
Year: 2016

Language: English
Pages: C, XIII,124
Tags: Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;Анализ выживаемости;