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Branch: Dauerleihe	Locations: MA-20 502 / Band fehlt o. Nachweis	Status: borrowed	Reservations: 0	Due date: 9/29/2044	Barcode: 00299359	Floor plans: Floor plan	Lending note:

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