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Joint models for longitudal and time-to-event data

with aplications in R
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Verfasser: Suche nach diesem Verfasser Rizopoulos, Dimitris (Verfasser)
Jahr: [2012]
Verlag: Boca Raton , London , New York, CRC Press Taylor & Francis
Reihe: Chapman & Hall-CRC biostatistics series
Mediengruppe: Dauerleihe
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Inhalt

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 of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models.
 
All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at:
http://jmr.r-forge.r-project.org/
TOC:
Table of Contents
 
Introduction
Inferential Objectives in Longitudinal Studies
Case Studies
Organization of the Book
 
Analysis of Longitudinal Data
Features of Repeated Measures Data
Linear Mixed Effects Models
Dropout in Longitudinal Studies
 
Analysis of Time-to-Event Data
Features of Event Time Data
Relative Risk Models
Time-Dependent Covariates
 
Joint Models for Longitudinal and Time-to-Event Data
The Standard Joint Model
Connection with the Dropout Framework
 
Extensions of the Standard Joint Model
Parameterizations
Multiple Failure Times
Latent Class Joint Models
 
Diagnostics
Residuals for the Longitudinal Submodel
Residuals for the Survival Submodel
Random Effects Distribution
 
Prediction and Accuracy in Joint Models
Dynamic Predictions for the Survival and Longitudinal Outcomes
Effect of the Parameterization on Predictions
Prospective Accuracy Measures for Longitudinal Markers
 

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Details

Verfasser: Suche nach diesem Verfasser Rizopoulos, Dimitris (Verfasser)
Verfasserangabe: Dimitris Rizopoulos
Jahr: [2012]
Verlag: Boca Raton , London , New York, CRC Press Taylor & Francis
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Systematik: Suche nach dieser Systematik MA-20, ME-40, BI-50
Interessenkreis: Suche nach diesem Interessenskreis Monographien
ISBN: 9781439872864
2. ISBN: 1439872864
Beschreibung: xvi, 261 Seiten, Diagramme
Reihe: Chapman & Hall-CRC biostatistics series
Schlagwörter: Datenverarbeitung; Epidemiologie; Biologie Methoden; Numerical analysis / Data processing / LC; R (Computer program language) / LC
Suche nach dieser Beteiligten Person
Sprache: Englisch
Mediengruppe: Dauerleihe