Evidence map›Paper›PMID 36793367›Full record

ArticleFrontiers in psychology2022

Analysis of proportions using arcsine transform with any experimental design.

Louis Laurencelle, Denis Cousineau

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–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

13 citing papers in PubMed.

  1. Article
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  3. Review
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  9. Review
  10. Article
  11. The Impact of ZnO and FePlants (Basel, Switzerland) · 2024
    Article
  12. Article
  13. Article
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

2 authors.

Louis LaurencelleDépartement des sciences de l'activité physique, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada.
Denis CousineauÉcole de psychologie, Université d'Ottawa, Ottawa, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Exact tests on proportions exist for single-group and two-group designs, but no general test on proportions exists that is appropriate for any experimental design involving more than two groups, repeated measures, and/or factorial designs. Method: Herein, we extend the analysis of proportions using arcsine transform to any sort of design. The resulting framework, which we have called Result: We illustrate the method with a few examples (single-factor design, two-factor design, within-subject design, and mixed design) and explore type I error rates with Monte Carlo simulations. We also examine power computation and confidence intervals for proportions. Discussion: ANOPA is a complete series of analyses for proportions, applicable to any design.

Indexed as

Anscombe transformarcsine transformfactorial designsproportionsrepeated-measure designs

Identifiers

PMID36793367
PMCPMC9922716

What OpenQuestion holds

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LicenceCC BY
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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.