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

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Image CAPTCHA

Enter the characters shown in the image.

User menu

You are here

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

TitleJoint Models for Longitudinal and Time-to-Event Data: With Applications in R
Publication TypeBook
Year of Publication2012
AuthorsRizopoulos, D
PublisherCRC Press
ISBN Number978-1-4398-7286-4
KeywordsMathematics / Probability & Statistics / General, Medical / Epidemiology, Science / Life Sciences / Biology
AbstractIn 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/