The DOI matches its Crossref record; 95 of the 100 references it cites were found in a registry or an index.
Analyzing longitudinal data with multilevel models: An example with individuals living with lower extremity intra-articular fractures.
Open accessAbstract
The use and quality of longitudinal research designs has increased over the past two decades, and new approaches for analyzing longitudinal data, including multi-level modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this paper is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham's Injury Control Research Center is analyzed using both SAS PROC MIXED and SPSS MIXED. We start our presentation with a discussion of data preparation for MLM analyses. We then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis such as online resources is provided at the end of the paper.
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“Multilevel models are highly flexible in handling daily-level missing data (Kwok et al., 2008)”
From Daily Communication Between First-Year College Students and Their Parents: Associations With Perceived Relationship Positivity (2024) · cites this paper as Kwok et al., 2008
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Analyzing longitudinal data with missing values
Enders, C. K. (2011) · Rehabilitation Psychology · doi:10.1037/a0025579 · Cited by 321
Hesser, H. (2015) · Internet Interventions · doi:10.1016/j.invent.2015.02.003 · Cited by 192
Analysis and interpretation of variability in soundscapes along an urban–rural gradient
Joo, W., Gage, S. H., & Kasten, E. P. (2011) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2011.08.001 · Cited by 174
Lapierre, L., van Steenbergen, E. F., Peeters, M. C. W., & Kluwer, E. S. (2015) · Journal of Organizational Behavior · doi:10.1002/job.2075 · Cited by 179
Finlay‐Jones, A., Kane, R., & Rees, C. (2017) · Journal of Clinical Psychology · doi:10.1002/jclp.22375 · Cited by 139
Metadata
- Authors
- Kwok, O.-M., Underhill, A. T., Berry, J. W., Luo, W., Elliott, T. R., & Yoon, M.
- Affiliations
- Texas A&M University (US)
- University of Alabama at Birmingham (US)
- University of Wisconsin–Milwaukee (US)
- Corresponding author
- Kwok, Oi-Man
- Venue
- Rehabilitation Psychology
- Published
- 2008-08
- Volume
- 53
- Issue
- 3
- Pages
- 370-386
- ISSN
- 0090-5550 (ISSN-L)
- 1939-1544
- PMC
- PMC2613314
- OpenAlex
- W2159072822
- Cited by
- 388
- References
- 100
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 10 · 2023: 21 · 2022: 28 · 2021: 52 · 2020: 30 · 2019: 33 · 2018: 26 · 2017: 25 · 2016: 30 · 2015: 31 · 2014: 22 · 2013: 16 · 2012: 12
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Rehabilitation Psychology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD039367)
- US Department of Health and Human Services (R49-CE000191)
- 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
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- multilevel modeling, longitudinal analysis, intra-articular fractures, lower limb fractures, latent growth curve models, linear growth model, covariance structure, nonlinear growth models, SAS PROC MIXED, data preparation
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