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Robust Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data

✍ Scribed by Ning Li; Robert M. Elashoff; Gang Li

Publisher: John Wiley and Sons
Year: 2009
Tongue: English
Weight: 159 KB
Volume: 51
Category: Article
ISSN: 0323-3847
DOI: 10.1002/bimj.200810491

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## Abstract Shared random effects joint models are becoming increasingly popular for investigating the relationship between longitudinal and time‐to‐event data. Although appealing, such complex models are computationally intensive, and quick, approximate methods may provide a reasonable alternative