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http://hdl.handle.net/1942/14735
Title: | The analysis of multivariate longitudinal data: a review | Authors: | VERBEKE, Geert FIEUWS, Steffen MOLENBERGHS, Geert Davidian, Marie |
Issue Date: | 2014 | Source: | Statistical methods in medical research, 23 (1), p. 42-59. | Abstract: | Longitudinal experiments often involve multiple outcomes measured repeatedly within a set of study participants. While many questions can be answered by modeling the various outcomes separately, some questions canonly be answered in a joint analysis of all of them. In this article, we will present a review of the many approaches proposed in the statistical literature. Four main model families will be presented, discussed and compared. Focus will be on presenting advantages and disadvantages of the different models rather than on the mathematical or computational details. | Notes: | Reprint Address: Verbeke, G (reprint author) - Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Louvain, Belgium. E-mail Addresses:geert.verbeke@med.kuleuven.be | Keywords: | mixed models; random effects; shared parameters; marginal models; conditional models; latent variables | Document URI: | http://hdl.handle.net/1942/14735 | ISSN: | 0962-2802 | e-ISSN: | 1477-0334 | DOI: | 10.1177/0962280212445834 | ISI #: | 000330776100003 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2015 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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workshop_rotterdam_verbeke_final.pdf | Peer-reviewed author version | 224.13 kB | Adobe PDF | View/Open |
0962280212445834.pdf Restricted Access | Published version | 182.02 kB | Adobe PDF | View/Open Request a copy |
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