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Random-Effects Models for Longitudinal Data
Nan M. Laird, James H. Ware. Biometrics, 1982-12-01
Topic: Risk, prevention and care in population studies
Models for the analysis of longitudinal data must recognize the relationship between serial observations on the same unit. Multivariate models with general covariance structure are often difficult to apply to highly unbalanced data, whereas two-stage random-effects models can be used easily. In two-stage models, the probability distributions for the response vectors of different individuals belong to a single family, but some random-effects parameters vary across individuals, with a distribution specified at the second stage. A general family of models is discussed, which includes both growth models and repeated-measures models as special cases. A unified approach to fitting these models, based on a combination of empirical Bayes and maximum likelihood estimation of model parameters and using the EM algorithm, is discussed. Two examples are taken from a current epidemiological study of the health effects of air pollution.
Why it matters
Describes random-effects models, a statistical approach for analyzing longitudinal data in which the same units are observed repeatedly. It is a general statistics paper; its examples come from a study of the health effects of air pollution.
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How this study scored 49/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on strength of evidence and institution's track record, so those were left out: it earned 45 of the 92 points we could judge it on, which is 49 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Biometrics) |
| Journal's citation record | 3 / 4 | Biometrics: journal h-index 405 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | — / 5 | No evidence rating recorded — left out of this score |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 1982 — older than 20 years, still counted |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 7 / 7 | Cited 8,941 times (OpenAlex, 2026-10-10) |
| Citations per year | 5 / 5 | 194.4 citations a year over 46 year(s) since 1982 |
| Impact for its field and year | 3 / 6 | Cited 7.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 4 / 4 | Cited 742 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author James H. Ware: h-index 84 (OpenAlex, whole career) |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 0 institution(s) in 0 countries — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 7168798) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 45 / 92 | Scored on 18 of 20 parts. We have no data for the rest, so they are left out: 45 of the 92 points we could judge it on is 49 out of 100. |
| Total | 49 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Laird, N. M., & Ware, J. H. (1982). Random-Effects Models for Longitudinal Data. Biometrics. https://doi.org/10.2307/2529876
Vancouver
Laird NM, Ware JH. Random-Effects Models for Longitudinal Data. Biometrics. 1982. doi:10.2307/2529876. PMID: 7168798.
BibTeX
@article{laird1982-7168798,
author = {Laird, Nan M. and Ware, James H.},
title = {{Random-Effects Models for Longitudinal Data}},
journal = {Biometrics},
year = {1982},
doi = {10.2307/2529876},
pmid = {7168798},
url = {https://doi.org/10.2307/2529876}
}