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Advances in Analysis of Longitudinal Data
Open accessAbstract
In this review, we explore recent developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives, including generalized estimating equations for analysis of longitudinal data. Methods are described for continuous and normally distributed as well as categorical (binary, ordinal, nominal) and count (Poisson) variables. Extensions of the model to three and four levels of clustering, multivariate outcomes, and incorporation of design weights are also described. Linear and nonlinear models are illustrated using an example involving a study of the relationship between mood and smoking.
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“To accommodate missing data, mixed models, which involve randomly deleting missing observations without dropping participants, will be used where appropriate in conducting primary analyses [70].”
From Acceptance and Commitment Therapy preceded by an experimental Attention Bias Modification procedure in recurrent depression: Study protocol for a randomized controlled trial (2018) · cites this paper as [70]
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Metadata
- Authors
- Gibbons, R. D., Hedeker, D., & DuToit, S.
- Affiliations
- University of Illinois Chicago (US)
- Venue
- Annual Review of Clinical Psychology
- Publisher
- Annual Reviews
- Published
- 2010-03-01
- Volume
- 6
- Issue
- 1
- Pages
- 79-107
- ISSN
- 1548-5943 (ISSN-L)
- 1548-5951
- PMC
- PMC2971698
- OpenAlex
- W2113413884
- Cited by
- 452
- References
- 75
- Citations by year
- 2026: 16 · 2025: 26 · 2024: 35 · 2023: 28 · 2022: 26 · 2021: 40 · 2020: 30 · 2019: 32 · 2018: 48 · 2017: 57 · 2016: 30 · 2015: 24 · 2014: 21 · 2013: 15 · 2012: 17
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annual Review of Clinical Psychology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (n44mh32056-10-0-1)
- National Institute of Mental Health (R01 MH8012201, N44 MH032056, R01MH080122)
- National Cancer Institute (P01CA098262, 5P01CA98262)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Agriculture, Soil, Plant Science
- Keywords
- longitudinal analysis, nonlinear mixed-effects models, generalized estimating equations, categorical outcomes, count data, Poisson regression, multilevel models, multivariate outcomes, design weights
- MeSH terms
- Humans, Longitudinal Studies, Models, Psychological, Psychology, Clinical
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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