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Joint Models for Longitudinal and Time-to-Event Data: With Applications in R book cover

1st Edition

Joint Models for Longitudinal and Time-to-Event Data With Applications in R

By Dimitris Rizopoulos Copyright 2012
278 Pages 36 B/W Illustrations
by Chapman & Hall

278 Pages 36 B/W Illustrations
by Chapman & Hall

275 Pages
by Chapman & Hall
Also available as eBook on:
In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment... Read more

Introduction. Analysis of Longitudinal Data. Analysis of Time-to-Event Data. Joint Models for Longitudinal and Time-to-Event Data. Extensions of the Standard Joint Model. Diagnostics. Survival Probabilities and Prospective Accuracy Measures.

Biography

Dimitris Rizopoulos is an Assistant Professor at the Department of Biostatistics of the Erasmus University Medical Center in the Netherlands. Dr. Rizopoulos received his M.Sc. in Statistics in 2003 from the Athens University of Economics and Business, and a Ph.D. in Biostatistics in 2008 from the Katholieke Universiteit Leuven.



Dr. Rizopoulos wrote his dissertation, as well as a number of methodological articles on various aspects of joint models for longitudinal and time-to-event data. He currently serves as an Associate Editor for Biometrics and Biostatistics, and has been a guest editor for a special issue in joint modeling techniques in Statistical Methods in Medical Research.

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