Home Contact Us Help Free delivery worldwide. Description Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography.
Journal of the Royal Statistical Society: The discussion includes parametric and semiparametric frailty models and accelerated failure time models. It is demanding for statistical practitioners and graduate students to grasp a good knowledge on frailty models from the existing literature. This book provides an in-depth discussion and explanation of the basics of frailty model methodology for such readers. For the purpose of sample size determination, we start with the simplest frailty model which is the parametric model with clusters sharing a frailty with a Gamma distribution. Then if subject i has m events,. The book starts with a brief overview of some basic concepts in classical survival analysis, collecting what is needed for the reading on the more complex frailty models.
A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data.
In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website. Product details Format Hardback pages Dimensions x x People who bought this also bought.
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The Frailty Model (Statistics for Biology and Health) [Luc Duchateau, Paul Janssen] on uzotoqadoh.tk *FREE* shipping on qualifying offers. Readers will find in. health and demography. Frailty models provide a powerful tool to analyse clustered survival data. Statistics for Biology and Health. Free Preview. © .
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Clinical Prediction Models Ewout W. This book provides an in-depth discussion and explanation of the basics of frailty model methodology for such readers. The discussion includes parametric and semiparametric frailty models and accelerated failure time models. Common techniques to fit frailty models include the EM-algorithm, penalised likelihood techniques, Laplacian integration and Bayesian techniques. More advanced frailty models for hierarchical data are also included.
Real-life examples are used to demonstrate how particular frailty models can be fitted and how the results should be interpreted. The programs to fit all the worked-out examples in the book are available from the Springer website with most of the programs developed in the freeware packages R and Winbugs. The book starts with a brief overview of some basic concepts in classical survival analysis, collecting what is needed for the reading on the more complex frailty models. He has collaborated extensively with physicians in oncology and allergy, public health workers and veterinarians, and is an author of numerous papers in statistical, medical and veterinarian journals.
He is an elected member of the International Statistical Institute.