Evidence map›Paper›PMID 35898418›Full record

ArticleEcology and evolution2022

Fixed or random? On the reliability of mixed-effects models for a small number of levels in grouping variables.

Johannes Oberpriller, Melina de Souza Leite, Maximilian Pichler

Abstract read
In one paragraph

Article in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Systematic review and meta-analysis of Murray's law in the coronary arterial circulation.American journal of physiology. Heart and circulatory physiology · 2024
    Pooled it
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  7. Co-Use of Some Substances Associated With Higher Doses in Adolescents: Findings From the Adolescent Brain Cognitive Development Study.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2026
    Article
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  19. Volitional spatial attention is lateralized in crows.Proceedings. Biological sciences · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Johannes OberprillerTheoretical Ecology University of Regensburg Regensburg Germany.ORCID https://orcid.org/0000-0001-6007-0041
Melina de Souza LeiteTheoretical Ecology University of Regensburg Regensburg Germany.ORCID https://orcid.org/0000-0003-0505-0667
Maximilian PichlerTheoretical Ecology University of Regensburg Regensburg Germany.ORCID https://orcid.org/0000-0003-2252-8327

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

fixed effectsgeneralized linear modelshierarchical modelsmixed‐effects modelsmultilevel modelsrandom effects

Identifiers

PMID35898418
PMCPMC9309037

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.