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Repeated measures data arise when the same characteristic is
measured on each case or subject at several times or under several
conditions. There is a multitude of techniques available for
analysing such data and in the past this has led to some confusion.
This book describes the whole spectrum of approaches, beginning
with very simple and crude methods, working through intermediate
techniques commonly used by consultant statisticians, and
concluding with more recent and advanced methods. Those covered
include multiple testing, response feature analysis, univariate
analysis of variance approaches, multivariate analysis of variance
approaches, regression models, two-stage line models, approaches to
categorical data and techniques for analysing crossover designs.
The theory is illustrated with examples, using real data brought to
the authors during their work as statistical consultants.
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.
Written for those who have taken a first course in statistical
methods, this book takes a modern, computer-oriented approach to
describe the statistical techniques used for the assessment of
reliability.
This text describes the statistical techniques used for the
assessment of reliability. Written for readers who have taken a
first course in statistical methods, it develops the specific
techniques used in reliability analysis from a modern,
computer-oriented viewpoint.
Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.
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.
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