CoChat
Sign Up
Cited by 994Meta-analysis and systematic reviewsPsychology Research and Bibliometricsscientometrics and bibliometrics research

The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.

Mini Meta‐Analysis of Your Own Studies: Some Arguments on Why and a Primer on How

Goh, Jin X., Hall, Judith A., Rosenthal, Robert·2016·Social and Personality Psychology Compass
DOI 10.1111/spc3.12267
Open this paper in CoChat — free account

Abstract

We outline the need to, and provide a guide on how to, conduct a meta‐analysis on one's own studies within a manuscript. Although conducting a “mini meta” within one's manuscript has been argued for in the past, this practice is still relatively rare and adoption is slow. We believe two deterrents are responsible. First, researchers may not think that it is legitimate to do a meta‐analysis on a small number of studies. Second, researchers may think a meta‐analysis is too complicated to do without expert knowledge or guidance. We dispel these two misconceptions by (1) offering arguments on why researchers should be encouraged to do mini metas, (2) citing previous articles that have conducted such analyses to good effect, and (3) providing a user‐friendly guide on calculating some meta‐analytic procedures that are appropriate when there are only a few studies. We provide formulas for calculating effect sizes and converting effect sizes from one metric to another (e.g., from Cohen's d to r ), as well as annotated Excel spreadsheets and a step‐by‐step guide on how to conduct a simple meta‐analysis. A series of related studies can be strengthened and better understood if accompanied by a mini meta‐analysis.

Overview

Integrity signals

Registry

Crossref · 10.1111/spc3.12267

Cites

59 of 59 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Flagged first, then by citations

Show all 58 references

Research works printed but not linked: 4

  1. Borenstein M., 2005, Comprehensive Meta‐analysis (version 3)
  2. Lai C. K., Reducing Implicit Racial Preferences: II
  3. Mosteller F. M., 1954, Handbook of Social Psychology: Volume I. Theory and Method
  4. Rosenthal R., 2008, Essentials of Behavioral Research

Cited by

Sorted by citations

Items 901–992 of 992

Related

See all

Metadata

Authors
Goh, J. X., Hall, J. A., & Rosenthal, R.
Affiliations
  • Northeastern University (US)
  • University of California, Riverside (US)
Corresponding author
Goh, Jin X.
ORCID
Venue
Social and Personality Psychology Compass
Publisher
Wiley
Published
2016-10
Volume
10
Issue
10
Pages
535-549
ISSN
1751-9004 (ISSN-L)
DOI
10.1111/spc3.12267
OpenAlex
W2527755291
Cited by
994
References
58
Citations by year
2026: 55 · 2025: 110 · 2024: 89 · 2023: 128 · 2022: 121 · 2021: 132 · 2020: 121 · 2019: 100 · 2018: 86 · 2017: 50 · 2016: 2
FWCI
74.11
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor, 1 d)
Locations
Social and Personality Psychology Compass (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
  • Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
Keywords
effect size estimation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review