The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Linear Models for the Analysis of Longitudinal Studies
Abstract
Longitudinal investigations play an increasingly prominent role in biomedical research. Much of the literature on specifying and fitting linear models for serial measurements uses methods based on the standard multivariate linear model. This article proposes a more flexible approach that permits specification of the expected response as an arbitrary linear function of fixed and time-varying covariates so that mean-value functions can be derived from subject matter considerations rather than methodological constraints. Three families of models for the covariance function are discussed: multivariate, autoregressive, and random effects. Illustrations demonstrate the flexibility and utility of the proposed approach to longitudinal analysis.
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Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
Self-citationA leisurely look at the bootstrap, the jackknife, and cross-validation
Efron, B., & Gong, G. (1983) · The American Statistician · doi:10.1080/00031305.1983.10483087 · Cited by 3,229
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
Harville, D. A. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480998 · Cited by 2,667
Cited by
Longitudinal data analysis using generalized linear models
LIANG, K.-Y., & ZEGER, S. L. (1986) · Biometrika · doi:10.1093/biomet/73.1.13 · Cited by 18,550
Gueorguieva, R., & Krystal, J. H. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.3.310 · Cited by 1,529
Context, composition and heterogeneity: using multilevel models in health research
Duncan, C., Jones, K., & Moon, G. (1998) · Social Science & Medicine · doi:10.1016/s0277-9536(97)00148-2 · Cited by 689
Ghisletta, P., & Spini, D. (2004) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986029004421 · Cited by 388
White, H., Pieper, C., & Schmader, K. (1998) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1998.tb04537.x · Cited by 323
Metadata
- Authors
- Ware, J. H.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1985-05
- Volume
- 39
- Issue
- 2
- Pages
- 95-101
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2038173886
- Cited by
- 483
- References
- 4
- FWCI
- 18.46
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
