Joint Models for Longitudinal and Time to Event Data

This book PDF is perfect for those who love Mathematics genre, written by Dimitris Rizopoulos and published by CRC Press which was released on 22 June 2012 with total hardcover pages 279. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Joint Models for Longitudinal and Time to Event Data books below.

Joint Models for Longitudinal and Time to Event Data
Author : Dimitris Rizopoulos
File Size : 42,8 Mb
Publisher : CRC Press
Language : English
Release Date : 22 June 2012
ISBN : 9781439872864
Pages : 279 pages
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Joint Models for Longitudinal and Time to Event Data by Dimitris Rizopoulos Book PDF Summary

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/

Joint Models for Longitudinal and Time to Event Data

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

Get Book
Joint Modeling of Longitudinal and Time to Event Data

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