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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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Cites
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
Research works printed but not linked: 7
- Allison, 1982, Sociological Methodology, 61
- Browne, 2004, MCMC Estimation in MLwiN
- Carpenter, 2004, Multiple imputation in MLwiN, Multilev. Modllng Newslett., 16, 9
- Rasbash, 2004, A User’s Guide to MLwiN, v2.0
- Shepherd, 1997, The National Child Development Study: an Introduction to the Origins of the Study and the Methods of Data Collection
- Spiegelhalter, 2000, WinBUGS Version 1.3 User Manual
- UK Data Archive, 2004, ESDS longitudinal, British Household Panel Survey; waves 1-11, 1991-2002: teaching dataset (social and political attitudes)
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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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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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