The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Multilevel Models for Longitudinal Data
Open accessAbstract
Summary Repeated measures and repeated events data have a hierarchical structure which can be analysed by using multilevel models. A growth curve model is an example of a multilevel random-coefficients model, whereas a discrete time event history model for recurrent events can be fitted as a multilevel logistic regression model. The paper describes extensions to the basic growth curve model to handle auto-correlated residuals, multiple-indicator latent variables and correlated growth processes, and event history models for correlated event processes. The multilevel approach to the analysis of repeated measures data is contrasted with structural equation modelling. The methods are illustrated in analyses of children’s growth, changes in social and political attitudes, and the interrelationship between partnership transitions and childbearing.
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“In the special case where an exposure is measured repeatedly over the life course, multilevel models could be used to overcome the problems caused by irregularly sampled measures, or missing measures, by estimating the exposure at common time points for all participants.22”
From A structured approach to hypotheses involving continuous exposures over the life course (2016) · cites this paper as [22]
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“This has the further benefit of reducing measurement error in the exposure.”
From A structured approach to hypotheses involving continuous exposures over the life course (2016) · cites this paper as [22]
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Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647
Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
Everitt, B. S. (2001) · Psychology Press eBooks · doi:10.4324/9781410605542-11 · Cited by 6,877
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012
Analysis of Incomplete Multivariate Data
Booth, D. E., & Schafer, J. L. (2000) · Technometrics · doi:10.2307/1271466 · Cited by 5,627
Goldstein, H. (2006) · Technometrics · doi:10.1198/tech.2006.s417 · Cited by 4,960
Diggle, P. J., Heagerty, P. J., Liang, K., & Zeger, S. L. (2002) · doi:10.1093/oso/9780198524847.001.0001 · Cited by 3,388
Gill, J. (2005) · Encyclopedia of Social Measurement · doi:10.1016/b0-12-369398-5/00166-3 · Cited by 3,126
Generalized Latent Variable Modeling
Skrondal, A., & Rabe‐Hesketh, S. (2004) · Chapman & Hall/CRC eBooks · doi:10.1201/9780203489437 · Cited by 2,299
Discrete-Time Methods for the Analysis of Event Histories
Allison, P. D. (1982) · Sociological Methodology · doi:10.2307/270718 · Cited by 2,080
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Fixed and random effects models: making an informed choice
Bell, A., Fairbrother, M., & Jones, K. (2019) · Quality & Quantity · doi:10.1007/s11135-018-0802-x · Cited by 1,085
The Great Recession and Fertility in Europe: A Sub-national Analysis
Matysiak, A., Sobotka, T., & Vignoli, D. (2021) · European Journal of Population · doi:10.1007/s10680-020-09556-y · Cited by 242
Howe, L., Tilling, K., Matijasevich, A., Petherick, E., Santos, A., Fairley, L., Wright, J., Santos, I., Barros, A., Martin, R. M., et al. (2013) · Statistical Methods in Medical Research · doi:10.1177/0962280213503925 · Cited by 193
Aging and Subjective Well-Being in Later Life
Jivraj, S., Nazroo, J. Y., Vanhoutte, B., & Chandola, T. (2014) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbu006 · Cited by 215
Identifying Critical Points of Trajectories of Depressive Symptoms from Childhood to Young Adulthood
Kwong, A. S. F., Manley, D., Timpson, N. J., Pearson, R. M., Heron, J., Sallis, H., Stergiakouli, E., Davis, O. S. P., & Leckie, G. (2019) · Journal of Youth and Adolescence · doi:10.1007/s10964-018-0976-5 · Cited by 193
Metadata
- Authors
- Steele, F.
- Affiliations
- University of Bristol (GB)
- Corresponding author
- Steele, Fiona
- Venue
- Journal of the Royal Statistical Society Series A (Statistics in Society)
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-10-29
- Volume
- 171
- Issue
- 1
- Pages
- 5-19
- ISSN
- 0964-1998 (ISSN-L)
- 1467-985X
- OpenAlex
- W2104023838
- Cited by
- 247
- References
- 35
- Citations by year
- 2026: 13 · 2025: 11 · 2024: 6 · 2023: 12 · 2022: 12 · 2021: 22 · 2020: 16 · 2019: 23 · 2018: 23 · 2017: 15 · 2016: 14 · 2015: 19 · 2014: 13 · 2013: 10 · 2012: 12
- FWCI
- 5.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the Royal Statistical Society Series A (Statistics in Society) (publishedVersion)
- London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion)
- Funders
- Economic and Social Research Council (ES/E00234X/1)
- 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
- multilevel models, longitudinal data, repeated measures, growth curve models, random coefficient models, event history models, recurrent events, multilevel logistic regression, autocorrelated residuals, structural equation modeling, child growth, attitude change, childbearing
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