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

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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 M...

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Autor principal: Rizopoulos, Dimitris
Lenguaje:eng
Publicado: CRC Press 2012
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/1487889
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author Rizopoulos, Dimitris
author_facet Rizopoulos, Dimitris
author_sort Rizopoulos, Dimitris
collection CERN
description 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
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institution Organización Europea para la Investigación Nuclear
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publishDate 2012
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spelling cern-14878892021-04-22T00:12:32Zhttp://cds.cern.ch/record/1487889engRizopoulos, DimitrisJoint Models for Longitudinal and Time-to-Event Data: With Applications in RMathematical Physics and Mathematics 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 CRC Pressoai:cds.cern.ch:14878892012
spellingShingle Mathematical Physics and Mathematics
Rizopoulos, Dimitris
Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title_full Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title_fullStr Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title_full_unstemmed Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title_short Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
title_sort joint models for longitudinal and time-to-event data: with applications in r
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1487889
work_keys_str_mv AT rizopoulosdimitris jointmodelsforlongitudinalandtimetoeventdatawithapplicationsinr

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