Evidence map›Paper›PMID 30142053›Full record

ArticleCBE life sciences education2018

Students Are Rarely Independent: When, Why, and How to Use Random Effects in Discipline-Based Education Research.

Elli Theobald

Abstract read
In one paragraph

Article in CBE life sciences education, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 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

58 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
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  11. Community college biology students' understanding ofJournal of microbiology & biology education · 2025
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  18. How students taking introductory biology experience the chemistry content.Journal of microbiology & biology education · 2024
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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

1 author.

Elli TheobaldDepartment of Biology, University of Washington, Seattle, WA 98195.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Discipline-based education researchers have a natural laboratory-classrooms, programs, colleges, and universities. Studies that administer treatments to multiple sections, in multiple years, or at multiple institutions are particularly compelling for two reasons: first, the sample sizes increase, and second, the implementation of the treatments can be intentionally designed and carefully monitored, potentially negating the need for additional control variables. However, when studies are implemented in this way, the observations on students are not completely independent; rather, students are clustered in sections, terms, years, or other factors. Here, I demonstrate why this clustering can be problematic in regression analysis. Fortunately, nonindependence of sampling can often be accounted for with random effects in multilevel regression models. Using several examples, including an extended example with R code, this paper illustrates why and how to implement random effects in multilevel modeling. It also provides resources to promote implementation of analyses that control for the nonindependence inherent in many quasi-random sampling designs.

Indexed as

Multilevel AnalysisStudentsCluster AnalysisHumansRandom AllocationResearch DesignScience

Identifiers

PMID30142053
PMCPMC6234830

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.