Request PDF on ResearchGate | Analysis of Multivariate Survival Data | Introduction.- Univariate survival data. Philip Hougaard at Lundbeck. Philip Hougaard. This book is, at it states in the preface, a tool box rather than a cookbook, for those wishing to analyse multivariate survival data. It would thus be. Analysis of Multivariate Survival Data. Philip Hougaard, Springer, New York, No. of pages: xvii+ Price: $ ISBN 0‐‐‐4.
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Code for statistical programs mostly in SAS, with some examples in Splus is given for some of the examples. There are exercises at the end of each chapter. The exercises at the end of the more applied chapters relate more to the identification of sources of bias, dependence mechanisms and time-frames, study design and choice of analysis. The aalysis of the theory includes a table outlining questions to consider when identifying the best model to use in a survial situation.
Analysis of Multivariate Survival Data – Philip Hougaard – Google Books
Review Text From the reviews: In addition it is a good reference to the technical literature available in this field. The first chapter briefly describes the main features of survival data, and the two main types of multivariate survival data parallel and longitudinal. Extending the Cox Model Terry Therneau. For some of the datasets, the data are given in the introduction in tabular form, so the reader could attempt to analyse the data and compare the results with those presented.
The chapter summary and bibliographic comments are also very useful. As the field is rather new, the concepts and the possible types of data are described in detail. The various datasets used as examples throughout the text are then detailed, and the five main pf of multivariate survival analysis presented in a table. Adequate up-to-date references are provided for interested readers to follow up if required. This book should prove an informative extension to the literature on survival analysis.
Some of the models in the latter chapters are more complex and less ready for practical use. The exercises at the end of each chapter makes it more useful Description Survival surviva, 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. The author’s discussion of time scales, the effect of censoring multivarite the role of covariates touch the very heart of survival analysis.
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This book is a long-awaited work that summarizes the state of the art of multivariate survival analysis and provides a valuable reference. The aim of the book is very clearly laid down. Statistical Methods in Bioinformatics Warren J.
I think that this book will be useful to statisticians who are dealing with modeling multivariate failure time data in their applied work. One of the most useful aspects of this book, in my opinion, is the extensive use made of practical examples.
This book is, at it states in the preface, a tool box rather than a cookbook, for those wishing to analyse multivariate survival data. Check out the top books of the year on our page Best Books of Unlike other books on survival, most of which have just one or two chapters dealing with multivariate material, this book is the first comprehensive treatment fully focusing on multivariate survival data This book is without any doubt an indispensable reading for both theoretical and practical statisticians.
Circulating vitamin D concentrations and risk of breast and prostate cancer: The Best Books of Survival Analysis David G. A table outlines the limitations of each of the four main approaches. There are exercises at the end of each chapter.
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Analysis of Multivariate Survival Data : Philip Hougaard :
This book extends the field by allowing for multivariate times. Other books in this series. Clinical Prediction Mmultivariate Ewout W. The book is a pleasure to read. The example discussed the most often, the Danish twins study, is one which will be of particular relevance to those involved in genetics studies.
Dispatched analyysis the UK in 1 business day When will my order arrive? The description of each dataset is helpfully cross-referenced to the later sections in which the dataset is analysed.
Analysis of Multivariate Survival Data
Receive exclusive offers and updates from Oxford Academic. In fact, this book will be most interesting for professional statisticians advancing to this field. This book should prove an informative extension to the literature on survival analysis. Every chapter contains an extensive summary which is very helpful A chapter describing various hhougaard of bivariate dependence follows.
Several of the exercises suggest analyses of specific datasets described in the introduction. Questions to consider before choosing between specific multi-state models, frailty models, marginal models and non-parametric approaches are considered in more detail in four separate tables.