Description
Survival Analysis with Interval-Censored Data
A Practical Approach with Examples in R, SAS, and BUGS
Chapman & Hall/CRC Interdisciplinary Statistics Series
Authors: Bogaerts Kris, Komarek Arnost, Lesaffre Emmanuel
Language: EnglishSubjects for Survival Analysis with Interval-Censored Data:
Keywords
Signal Tandmobiel Study; Accelerated Failure Time Model; signal; HPD Credible Interval; tandmobiel; Interval Censored Survival Times; study; MCMC Procedure; Arnošt Komk; Aft Model; Emmanuel Lesaffre; Data Set; Marc van Kreveld; SAS Macro; Parametric Aft Model; Frailty Model; HPD Interval; Weibull Aft Model; MCMC Sampling; PH Model; LIFEREG Procedure; Posterior Summary Statistics; Interval Censoring; Weighted Log Rank Tests; Shared Frailty Model; Posterior Predictive Density; Log Rank Test; Frailty Distribution; Baseline Hazard; Log Normal Model; Generalized Log Rank Tests
57.55 €
In Print (Delivery period: 14 days).
Add to cart the book of Bogaerts Kris, Komarek Arnost, Lesaffre EmmanuelPublication date: 06-2020
· 15.6x23.4 cm · Paperback
80.97 €
In Print (Delivery period: 15 days).
Add to cart the book of Bogaerts Kris, Komarek Arnost, Lesaffre EmmanuelPublication date: 12-2017
326 p. · 15.6x23.4 cm · Hardback
Description
/li>Contents
/li>Readership
/li>Biography
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Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice.
Features:
-Provides an overview of frequentist as well as Bayesian methods.
-Include a focus on practical aspects and applications.
-Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website.
The authors:
Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials.
Arnošt Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal.
Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA.
Introduction. Inference for Right-Censored Data. Estimation of the Survival Distribution. Comparison of Two or More Survival Distributions. Proportional Hazard Model. Accelerated Failure Time Model. Bivariate Interval-Censored Data. More Complex Problems. Other Topics in Interval Censoring.