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

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/

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Series:	Chapman & Hall/CRC Biostatistics Series
Release date:	2023
Authors:	Dimitris Rizopoulos
Dimensions:	234 x 156mm (L x W)
Format:	Paperback
Pages:	278
ISBN-13:	978-1-03-247756-5
Categories:	Books > Medicine > General issues > Medical equipment & techniques > Medical research Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
LSN:	1-03-247756-3
Barcode:	9781032477565

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