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The analysis of multivariate longitudinal data: A review
Open accessAbstract
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 can only 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.
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“As noted in the review by Verbeke et al. (2014), copula models have been utilized in the multivariate longitudinal data literature although it is not widely used in biomedical applications; early contributions include Frees and Wang (2005), Lambert (1996), Lambert and Vandenhende (2002), and Meester and Mackay (1994).”
From Dependence modeling of multivariate longitudinal hybrid insurance data with dropout (2021) · cites this paper as Verbeke et al. (2014)
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Metadata
- Authors
- Verbeke, G., Fieuws, S., Molenberghs, G., & Davidian, M.
- Affiliations
- Hasselt University (BE)
- KU Leuven (BE)
- North Carolina State University (US)
- Corresponding author
- Verbeke, Geert
- Venue
- Statistical Methods in Medical Research
- Publisher
- SAGE Publications
- Published
- 2012-04-20
- Volume
- 23
- Issue
- 1
- Pages
- 42-59
- ISSN
- 0962-2802 (ISSN-L)
- 1477-0334
- PMC
- PMC3404254
- OpenAlex
- W2004277545
- Cited by
- 290
- References
- 102
- Citations by year
- 2026: 8 · 2025: 25 · 2024: 17 · 2023: 19 · 2022: 30 · 2021: 43 · 2020: 34 · 2019: 26 · 2018: 19 · 2017: 19 · 2016: 20 · 2015: 14 · 2014: 13 · 2013: 3
- FWCI
- 9.16
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Statistical Methods in Medical Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Document Server@UHasselt (UHasselt) (submittedVersion, other-oa)
- Lirias (submittedVersion)
- Funders
- National Cancer Institute (R01CA085848, P01CA142538)
- National Institute of Allergy and Infectious Diseases (R37AI031789)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- multivariate longitudinal data, joint modeling, multiple outcomes, repeated measures, longitudinal experiment, model comparison
- MeSH terms
- Hearing, Humans, Longitudinal Studies, Models, Statistical, Multivariate Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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