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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This book should prove an informative extension to the literature on survival analysis. In addition it is a good reference to the technical literature available in this field. Close mobile search navigation Article navigation. Looking for beautiful books? Survival Analysis David G. Four different approaches to the analysis of such data are presented from an applied point of view. The chapter summary and bibliographic comments are also very useful. Analyzing Ecological Data Alain F.

These would be of most use for those seeking to understand fully the underlying mathematical statistics of these models. 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 Poor diet quality in pregnancy is associated with increased risk of excess fetal growth: The datasets are described fully in the introduction, and include several examples of each of the more common types of multivariate data.

Throughout the book theoretical developments are extensively exemplified by real-life examples and computational aspects are dealt with as well. This book is, at it states in the preface, a tool box rather than a cookbook, for those wishing to analyse multivariate survival data. The example discussed the most often, the Danish twins study, is one which will be of particular relevance to those involved in genetics studies.


One of the most useful aspects of this book, in my opinion, is the extensive use made of practical examples. The chapter concludes with a summary of the datasets discussed throughout the text, discussing the main questions and which models are used to answer them.

Sign In or Create an Account. Regression Methods in Biostatistics Eric Vittinghoff. The various datasets used as examples throughout the text are ov detailed, and the five main aims of multivariate survival analysis presented in a table.

The book divides into three main sections: Home Contact Us Help Free delivery worldwide. I think that this analysiis will be useful to statisticians who are dealing with modeling multivariate failure time data in their applied work.

Anyone considering writing the second book has a hard act to follow – this sets a very high standard and is recommended for all statisticians with an interest in survival analysis techniques. His insights into the nature of dependence extend far beyond survival analysis and touch some of the most fundamental aspects of our discipline. A chapter describing various measures of bivariate dependence follows. As the field is rather new, the concepts and the possible types of data are described in detail.

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.

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. Socioeconomic position during pregnancy and DNA methylation signatures at three stages across early life: Logistic Regression David G.

Analysis of Multivariate Survival Data

The first chapter briefly describes the main features of survival data, and the two main types of multkvariate survival data parallel and longitudinal. Review Text From the reviews: The main part of the book consists of ten chapters hougaafd each of the four main approaches to multivariate survival analysis: Dispatched from the UK in 1 business day When will my order arrive? The author’s discussion of time scales, the effect of censoring and the role of covariates touch the very heart of survival analysis.


Product details Format Hardback pages Dimensions x x Oxford University Press is a department of the University of Oxford.

Every chapter contains a set of exercises suitable to practice These chapters contain much theoretical development, including statistical derivation and issues around estimation of the various models, and are more mathematically-orientated than the rest of the book.

These datasets are analysed throughout the text, and results from the various different models presented, interpreted and compared. Description 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.

In the case of the main chapters describing the different approaches, these are theoretically-based, and include examples of deriving transition probabilities for the multi-state model and survivor functions frailty models. The Best Books of The summary of the theory includes a table outlining questions to consider when identifying the best model to use in a given situation.

Analysis of Multivariate Survival Data : Philip Hougaard :

A table outlines the limitations of each of the four main approaches. Extending the Cox Model Terry Therneau. There are exercises at the end of each chapter. Analysis of Multivariate Survival Data.