ANALYSIS OF MULTIVARIATE SURVIVAL DATA HOUGAARD PDF

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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Every chapter contains an extensive summary which is very helpful Analysis of Multivariate Survival Data. As the field is rather new, the concepts and the possible types of data are described in detail.

The organization of the book, and the good use of cross-referencing, mean that it can be read in varying degrees of depth. These datasets are analysed throughout the text, and results from the various different models presented, interpreted and compared. It would thus be of most relevance to applied statisticians or epidemiologists requiring a theoretical and practical grounding in the analysis of such data.

The last chapter provides a very useful summary of the text, with cross-references to the appropriate sections throughout. Citing articles via Google Scholar. Survival Analysis John P. A chapter describing various measures of bivariate dependence follows. Check out the top books of the year on dat page Best Books of The book is a pleasure to read.

Analysis of Multivariate Survival Data

The chapter summary and hoygaard comments are also very useful. Statistical Methods in Bioinformatics Warren J. Oxford University Press is a department of the University of Oxford. The aim of the book is very clearly laid down. This book is without any doubt an indispensable reading for both theoretical and practical statisticians. Other books in this series.

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By using our website you agree to our use of cookies. Dispatched from the UK in 1 business day When will my order arrive? 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 A practical section on the course of analysis includes tables and discussion of which models are appropriate for which type of data and the relevance of each approach for various purposes.

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Description Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, naalysis, and demography, but previously standard methods have requested that all time hougaarr are univariate and independent. This book should prove an informative extension to the literature on survival analysis. Home Contact Us Help Free delivery worldwide. Analyzing Ecological Data Alain F. The datasets are described fully in the introduction, and include several examples of each of the more common types of multivariate data.

Various aspects of og theory and statistical inference for each of these approaches are discussed, including helpful sections on assessing goodness-of-fit and choosing between the different models available within each approach. The book lf into three main sections: Throughout the book theoretical developments are extensively exemplified by real-life examples and computational aspects are dealt with as well. These would be of most use for those seeking to understand fully the underlying mathematical statistics of these models.

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There are exercises at the end of each chapter. I believe this to be the first book on multivariate survival.

Analysis of Multivariate Survival Data : Philip Hougaard :

Product details Format Hardback pages Dimensions x x Survival Analysis David G. Clinical Prediction Models Ewout W. The author’s discussion of time scales, the effect of censoring and the role of covariates touch the very heart of survival analysis.

There are exercises at the end of each chapter. Extending the Cox Model Terry Therneau.

Review Text From the reviews: Poor diet quality in pregnancy is associated with increased risk of excess fetal growth: Code for statistical programs mostly in SAS, with some examples in Splus is given for some of the examples. Receive exclusive offers and survial from Oxford Academic.

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 level of mathematical detail is nice I think that this book will be useful to statisticians who are dealing with modeling multivariate failure time data in survivsl applied work.

In addition it is a good reference to the technical literature available in this field.