"Preface This book is an outgrowth of Classical Competing Risks (2001). I was very pleased to be encouraged by Rob Calver and Jim Zidek to write a second, expanded edition. Among other things it gives the opportunity to correct the many errors that crept into the first edition. This edition has been
Multivariate Survival Analysis and Competing Risks
โ Scribed by Martin J. Crowder
- Publisher
- Chapman and Hall/CRC
- Year
- 2012
- Tongue
- English
- Leaves
- 395
- Series
- Chapman & Hall/CRC Texts in Statistical Science
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods.
There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.
๐ SIMILAR VOLUMES
Increasingly, researchers need to perform multivariate statistical analyses on their data. Unfortunately, a lack of mathematical training prevents many from taking advantage of these advanced techniques, in part, because books focus on the theory and neglect to explain how to perform and interpret m
<p>Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariat