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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Analysis of Multivariate Survival Data. | International Journal of Epidemiology | Oxford Academic
These would be of most use for those seeking to understand fully the underlying mathematical statistics of these models. Check out the top books of the year on our page Best Books of Questions to consider before choosing between specific multi-state models, frailty models, marginal models and survivwl approaches are considered in more detail in four separate tables. 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.
Code for statistical programs mostly in SAS, with some examples in Splus is given for some of the examples. It would thus be of most relevance to applied statisticians or epidemiologists requiring a theoretical and practical grounding in the analysis of such data.
Statistical Methods in Bioinformatics Warren J.
Analysis of Multivariate Survival Data : Philip Hougaard :
The book divides into three main sections: The summary of the theory includes a table outlining multivvariate to consider when identifying the best model to use in a given situation. This book extends the field by allowing for multivariate times. This book should prove an informative extension to the literature on survival analysis.
Survival Analysis John P. The datasets are described fully in the introduction, and include several examples of each of the more common types of multivariate data.
The three dependence mechanisms—common events, common risks and event-related dependence—are outlined in a non-mathematical chapter, with a useful table showing common data types relating to these three mechanisms. There are exercises at the end of each chapter. Close mobile search navigation Article navigation. One of the most useful aspects of this book, in my opinion, is the extensive use made of practical examples.
His insights into the nature of dependence extend far beyond survival analysis and touch some of the most fundamental aspects of our discipline. Visit our Beautiful Books page and find lovely books for kids, photography lovers and more.
Analysis of Multivariate Survival Data
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. A chapter summarizing approaches mulrivariate univariate survival data follows, with indications as to which sections are most important as forming the basis for development of the different multivariate models.
The chapter summary and bibliographic comments are also very useful. A chapter describing various measures analysks bivariate dependence follows.
Adequate up-to-date references are provided for analjsis readers to follow up if required. Home Contact Us Help Free delivery worldwide. Product details Format Hardback pages Dimensions x x Every chapter contains a set of exercises suitable to practice Review Text From the reviews: Regression Methods in Biostatistics Eric Vittinghoff.
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.
The level of mathematical detail is nice In addition it is a good reference to og technical literature available in this field.
The organization of the book, and the good use of cross referencing, mean that it can be read in varying degrees of depth. A table outlines the limitations of each of the four main approaches. The aim of the book is very clearly laid down. The main part of the book consists of ten chapters outlining each of the four main approaches to multivariate survival analysis: 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.
Four different approaches to the analysis of such data are presented from an applied point of view. In fact, this anaylsis will be most interesting for professional statisticians advancing to this field.
Other books in this series. Various aspects of the surgival and statistical inference for each of these approaches are discussed, including helpful sections on assessing goodness-of-fit and anaalysis between the different models available within each approach.
There are exercises at the end of each chapter. This book is without any doubt an indispensable reading for both theoretical and practical statisticians. 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. 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.
Dispatched from the UK in 1 business day When will my order arrive? Circulating vitamin D concentrations and risk of breast and prostate cancer: I believe this to be the first book on multivariate survival. Houaard chapter contains an extensive summary which is very helpful The book is a pleasure to read.