Modeling Discrete Time-to-Event Data (Hardcover, 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Series in Statistics
Release date:	June 2016
First published:	2016
Authors:	Gerhard Tutz • Matthias Schmid
Dimensions:	235 x 155 x 21mm (L x W x T)
Format:	Hardcover
Pages:	247
Edition:	1st ed. 2016
ISBN-13:	978-3-319-28156-8
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Promotions
LSN:	3-319-28156-9
Barcode:	9783319281568

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