Selection Method Approaches
Abstract
This chapter contains sections titled: Introduction Effect Size Models for Selection Bias Specifying Selection Models Methods that Assume a Known Selection Model Methods for Weight Functions that Depend only on the p-Value Methods for Weight Functions that Depend on both T and σ Applying Weight Function Models in Practical Meta-Analysis How Well do Weight Function Models Work? Examples Conclusions and Recommendations References
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A general reason to expect small-study effects is that researchers often perform statistical power analyses before an intervention; small studies will have larger effects if researchers are reasonably good at guessing effect sizes.
“A general reason to expect small‐study effects is that researchers often perform statistical power analyses before embarking on an intervention. As interventions with large expected effects require smaller sample sizes for a given level of power, small studies will have larger effects if researchers are reasonably good at guessing the effect sizes (Hedges & Vevea, 2005).”
From Targeted school‐based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K‐6: A systematic review (2021) · cites this paper as Hedges & Vevea, 2005
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Cited by 123
- Authors
- Hedges, L. V., & Vevea, J.
- Affiliations
- University of Chicago (US)
- University of California, Santa Cruz (US)
- ORCID
- Hedges, Larry V.
- Venue
- Publication Bias in Meta‐Analysis
- Publisher
- Wiley
- Published
- 2005-10-07
- Pages
- 145-174
- OpenAlex
- W1508569606
- Cited by
- 123
- References
- 0
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 8 · 2023: 8 · 2022: 8 · 2021: 11 · 2020: 5 · 2019: 6 · 2018: 9 · 2017: 7 · 2016: 4 · 2015: 22 · 2014: 8 · 2013: 2 · 2012: 5
- Type
- other
- Language
- en
- Open access
- closed
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- selection bias, selection model, weight functions, p-values, meta-analysis, publication bias
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