Tutz Modeling Discrete Time-to-Event Data 9783319281568

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Автор: Tutz
Название: Modeling Discrete Time-to-Event Data
ISBN: 9783319281568
Издательство: Springer
Классификация:

Вероятность и статистика

ISBN-10: 3319281569
Обложка/Формат: Hardback
Страницы: 247
Вес: 0.55 кг.
Дата издания: 2016
Серия: Springer Series in Statistics
Язык: English
Иллюстрации: 55 black & white illustrations, 3 colour illustrations, biography
Размер: 166 x 242 x 21
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book.
Дополнительное описание: Introduction.- The Life Table.- Basic Regression Models.- Evaluation and Model Choice.- Nonparametric Modelling and Smooth Effects.- Tree-Based Approaches.- High-Dimensional Models - Structuring and Selection of Predictors.- Competing Risks Models.- Multi

Modeling Discrete Time-to-Event Data, Tutz