The DOI matches its Crossref record; 116 of the 116 references it cites were found in a registry or an index.
Best practice guidance for linear mixed-effects models in psychological science
Open accessAbstract
The use of Linear Mixed-effects Models (LMMs) is set to dominate statistical analyses in psychological science and may become the default approach to analyzing quantitative data. The rapid growth in adoption of LMMs has been matched by a proliferation of differences in practice. Unless this diversity is recognized, and checked, the field shall reap enormous difficulties in the future when attempts are made to consolidate or synthesize research findings. Here we examine this diversity using two methods – a survey of researchers (n = 163) and a quasi-systematic review of papers using LMMs (n = 400). The survey reveals substantive concerns among psychologists using or planning to use LMMs and an absence of agreed standards. The review of papers complements the survey, showing variation in how the models are built, how effects are evaluated and, most worryingly, how models are reported. Using these data as our departure point, we present a set of best practice guidance, focusing on the reporting of LMMs. It is the authors’ intention that the paper supports a step-change in the reporting of LMMs across the psychological sciences, preventing a trajectory in which findings reported today cannot be transparently understood and used tomorrow.
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Cites
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Cited by
An Introduction to Linear Mixed-Effects Modeling in R
Brown, V. A. (2021) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245920960351 · Cited by 576
Do, H. J., Kong, H.-K., Tetali, P., Lee, J., & Bailey, B. P. (2023) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3579532 · Cited by 32
The That-Trace Effect: Evidence from Spanish–English Code-Switching
Hoot, B., & Ebert, S. (2021) · Languages · doi:10.3390/languages6040189 · Cited by 9
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Metadata
- Authors
- Meteyard, L., & Davies, R. A. I.
- Venue
- Journal of Memory and Language
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 112
- Pages
- 104092
- ISSN
- 0749-596X (ISSN-L)
- OpenAlex
- W2920871702
- Cited by
- 698
- References
- 116
- FWCI
- 47.51
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
