Evidence map›Paper›PMID 38345247›Full record

ReviewPersonality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc2024

Power to Detect What? Considerations for Planning and Evaluating Sample Size.

Roger Giner-Sorolla, Amanda K Montoya, Alan Reifman, Tom Carpenter, Neil A Lewis, Christopher L Aberson, Dries H Bostyn, Beverly G Conrique, Brandon W Ng, Alexander M Schoemann and 1 more

Open access · hybridAbstract readReview
In one paragraph

Review in Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
170.9field-weighted citation impact, top 1% of its field
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

66 citing papers in PubMed, 1 synthesis or guideline pooled it, 162 citations in OpenAlex.

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  7. Evaluating the age of rib fractures throughInternational journal of legal medicine · 2026
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6 more citing papers are in PubMed but not listed here.

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

11 authors at 11 institutions in 3 countries.

Roger Giner-SorollaUniversity of Kent, Canterbury, UK.
Amanda K MontoyaUniversity of California, Los Angeles, USA.
Alan ReifmanTexas Tech University, Lubbock, USA.
Tom CarpenterSeattle Pacific University, WA, USA.
Neil A LewisCornell University & Weill Cornell Medical College, Ithaca, NY, USA.ORCID 0000-0001-7912-1689
Christopher L AbersonHumboldt State University, Arcata, CA, USA.
Dries H BostynGhent University, Belgium.
Beverly G ConriqueUniversity of Pittsburgh, PA, USA.
Brandon W NgUniversity of Richmond, VA, USA.
Alexander M SchoemannEast Carolina University, Greenville, NC, USA.
Courtney SoderbergCenter for Open Science, Charlottesville, VA, USA.
Cal Poly Humboldt · USCenter for Open Science · USCornell University · USEast Carolina University · USGhent University Hospital · BESeattle Pacific University · USTexas Tech University · USUniversity of California, Los Angeles · USUniversity of Kent · GBUniversity of Pittsburgh · USUniversity of Richmond · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

academic abstractIn the wake of the replication crisis, social and personality psychologists have increased attention to power analysis and the adequacy of sample sizes. In this article, we analyze current controversies in this area, including choosing effect sizes, why and whether power analyses should be conducted on already-collected data, how to mitigate the negative effects of sample size criteria on specific kinds of research, and which power criterion to use. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings), given the limitations of interest-based minimums or field-wide effect sizes. We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology. PUBLIC ABSTRACT: Recently, social-personality psychology has been criticized for basing some of its conclusions on studies with low numbers of participants. As a result, power analysis, a mathematical way to ensure that a study has enough participants to reliably "detect" a given size of psychological effect, has become popular. This article describes power analysis and discusses some controversies about it, including how researchers should derive assumptions about effect size, and how the requirements of power analysis can be applied without harming research on hard-to-reach and marginalized communities. For novel research questions, we advocate that researchers base sample sizes on effects that are likely to be cost-effective for other people to implement (in applied settings) or to study (in basic research settings). We discuss two alternatives to power analysis, precision analysis and sequential analysis, and end with recommendations for improving the practices of researchers, reviewers, and journal editors in social-personality psychology.

Indexed as

Research DesignHumansPsychology, SocialSample Sizepower analysisresearch methodssample sizestatistics

Identifiers

PMID38345247
PMCPMC11193916
OpenAlexW4391754649

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.