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Dimitris Rizopoulos - Joint Models for Longitudinal and Time-to-Event Data: With Applications in R - 9781439872864 - V9781439872864
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Joint Models for Longitudinal and Time-to-Event Data: With Applications in R

€ 108.31
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Description for Joint Models for Longitudinal and Time-to-Event Data: With Applications in R Hardback. Series: Chapman & Hall/CRC Biostatistics Series. Num Pages: 275 pages, 36 black & white illustrations, 6 black & white tables. BIC Classification: MBGR; MBNS. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 162 x 21. Weight in Grams: 550.
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 ... Read more

Product Details

Publisher
Taylor & Francis Ltd United States
Number of pages
275
Format
Hardback
Publication date
2012
Series
Chapman & Hall/CRC Biostatistics Series
Condition
New
Number of Pages
275
Place of Publication
, United States
ISBN
9781439872864
SKU
V9781439872864
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-2

About Dimitris Rizopoulos
Dimitris Rizopoulos is an Assistant Professor at the Department of Biostatistics of the Erasmus University Medical Center in the Netherlands. Dr. Rizopoulos received his M.Sc. in Statistics in 2003 from the Athens University of Economics and Business, and a Ph.D. in Biostatistics in 2008 from the Katholieke Universiteit Leuven. Dr. Rizopoulos wrote his dissertation, ... Read more

Reviews for Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
Overall, the book provides a nice introduction to joint models and the R package JM . It is well written, readable, and comprehensive. With the availability of the R package for joint models, it is expected that joint models will become increasingly popular in practice, especially in medical research. In summary, the book makes an important contribution to the ... Read more

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


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