This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.
R is a statistical computer program used and developed by statisticians around the world. It is probably the leading statistical program, at least among statisticians, and it is freely available. A First Guide to Statistical Computations in R is intended for the newcomer who wants to do statistical analysis with R and needs a guide to get started. The book focuses on statistical data problems that are often encountered within the biosceinces. It puts special emphasis on linear models and analysis of repeated measurements data, but also deals with binary data and survival data, among others. Problems are presented and solutions - along with the corresponding OR code and output - are provided. The guide is divided into two parts: the first part on R basics and the second part on the statistical analyses using R. Various datasets are used for illustration and they are all available in the R package Guide1data.
R is a statistical computer program used and developed by statisticians around the world. It is probably the leading statistical program, at least among statisticians, and it is freely available. A First Guide to Statistical Computations in R is intended for the newcomer who wants to do statistical analysis with R and needs a guide to get started. The book focuses on statistical data problems that are often encountered within the biosceinces. It puts special emphasis on linear models and analysis of repeated measurements data, but also deals with binary data and survival data, among others. Problems are presented and solutions - along with the corresponding OR code and output - are provided. The guide is divided into two parts: the first part on R basics and the second part on the statistical analyses using R. Various datasets are used for illustration and they are all available in the R package Guide1data.
This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.
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