Oberpriller, Johannes and Leite, Melina de Souza and Pichler, Maximilian (2022) Fixed or random? On the reliability of mixed-effects models for a small number of levels in grouping variables. ECOLOGY AND EVOLUTION, 12 (7): e9062. ISSN 2045-7758,
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Biological data are often intrinsically hierarchical (e.g., species from different genera, plants within different mountain regions), which made mixed-effects models a common analysis tool in ecology and evolution because they can account for the non-independence. Many questions around their practical applications are solved but one is still debated: Should we treat a grouping variable with a low number of levels as a random or fixed effect? In such situations, the variance estimate of the random effect can be imprecise, but it is unknown if this affects statistical power and type I error rates of the fixed effects of interest. Here, we analyzed the consequences of treating a grouping variable with 2-8 levels as fixed or random effect in correctly specified and alternative models (under- or overparametrized models). We calculated type I error rates and statistical power for all-model specifications and quantified the influences of study design on these quantities. We found no influence of model choice on type I error rate and power on the population-level effect (slope) for random intercept-only models. However, with varying intercepts and slopes in the data-generating process, using a random slope and intercept model, and switching to a fixed-effects model, in case of a singular fit, avoids overconfidence in the results. Additionally, the number and difference between levels strongly influences power and type I error. We conclude that inferring the correct random-effect structure is of great importance to obtain correct type I error rates. We encourage to start with a mixed-effects model independent of the number of levels in the grouping variable and switch to a fixed-effects model only in case of a singular fit. With these recommendations, we allow for more informative choices about study design and data analysis and make ecological inference with mixed-effects models more robust for small number of levels.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | ANOVA; VARIANCE; ECOLOGY; OVERDISPERSION; FLEXIBILITY; ERROR; REML; fixed effects; generalized linear models; hierarchical models; mixed-effects models; multilevel models; random effects |
| Subjects: | 500 Science > 580 Botanical sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Pflanzenwissenschaften > Group Theoretical Ecology (Prof. Dr. Florian Hartig) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 09 Jan 2024 08:18 |
| Last Modified: | 09 Jan 2024 08:18 |
| URI: | https://pred.uni-regensburg.de/id/eprint/57092 |
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