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CRC Joint Models for Longitudinal and Time-to-Event Data pdf

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  • TA的每日心情
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    2016-3-19 06:18
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    [LV.4]偶尔看看III

    发表于 2018-5-5 12:55:35 | 显示全部楼层 |阅读模式
    Joint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series)
    by Dimitris Rizopoulos  (Author)

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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 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/

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  • TA的每日心情
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    2017-7-5 13:19
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    [LV.6]常住居民II

    发表于 2018-5-5 19:18:30 | 显示全部楼层
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  • TA的每日心情
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    2018-11-22 08:46
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    [LV.10]以坛为家III

    发表于 2018-5-15 15:19:24 | 显示全部楼层
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