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The Study

A Comparative Evaluation of Psychometric Meta‐Analysis Methods in Management and Applied Psychology: Toward a Nuanced Understanding of Their Accuracy

In simple terms

This study is like a computer game that tests different math tools for combining research results. It shows which tool worked best in the game, but we don’t know if it will work the same way with real studies.

0%

Analysis score

0/ 0

Maximum 0 for a computational/algorithm study.

Where the score came from

Reporting0
Methodology0
Publication100
Statistical54
Study type (basis of the score)
Computational/Algorithm Study
Level 5 - Expert opinion
What’s the bottom line?

Scientists made fake data to test five ways of combining study results to find the true effect. They checked which method guessed best.

Where does this study sit?

Reviews of RCTs (Meta-analyses)

Max 100

Randomized Trials

Max 90

Reviews of Cohort Studies

Max 85

Cohort Studies

Max 72

Reviews of Case-Control Studies

Max 63

Case-Control Studies

Max 58

Cross-Sectional & Case Series

Max 50

Expert Opinion

Max 5
StrongerWeaker
Expert Opinion
Level 5
0

0 / 100

Quality score

Based on clinical experience or non-systematic literature reviews. The lowest level of evidence as they are most susceptible to bias and personal perspective.

Cannot establish causation

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Key takeaways

Summary

Based on the study abstract and findings.

  1. 1The results suggest that while all random-effects methods work well, choosing the right one can slightly improve accuracy when combining study results in psychology and management.
  2. 2All random-effects methods guessed the average effect well.
  3. 3The best one used Schmidt and Hunter's method with special weights.
  4. 4Differences between methods were tiny.

Score breakdown, methodology, conflicts of interest, evidence analysis & raw study data

Publication

Journal

Personnel Psychology

Year

2025

Authors

In‐Sue Oh, Huy Le, Frank L. Schmidt

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