The Cox Model And Its Applications (springerbriefs In Statistics)
by Mikhail Nikulin /
2016 / English / PDF
2.4 MB Download
This book will be of interest to readers active in the fields of
survival analysis, genetics, ecology, biology, demography,
reliability and quality control.
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.
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.
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.
