Beyond power calculations¶
Gelman, A., & Carlin, J. (2014). Beyond power calculations: Assessing Type S (sign) and Type M (magnitude) errors. Perspectives on Psychological Science, 9(6), 641-651.
Cited by¶
4 citations across 4 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Effect Size
- Gelman and Carlin's 2014 extension into "Type M" (magnitude) and "Type S" (sign) errors showed mathematically that underpowered studies reaching statistical significance tend to dramatically exaggerate the true effect size (a "winner's curse" phenomenon)
This sourceIntroduces Type M (exaggeration) and Type S (sign) errors and shows underpowered significant studies exaggerate true effect size — the correct source for marker 072. Replaces the mis-keyed greenland-2016 (which is about P-value misinterpretation, not Type M/S).
- Gelman and Carlin's 2014 extension into "Type M" (magnitude) and "Type S" (sign) errors showed mathematically that underpowered studies reaching statistical significance tend to dramatically exaggerate the true effect size (a "winner's curse" phenomenon)
- Regression to the Mean
- T4 — Name: RTM in Replication and Winner's-Curse Contexts. RTM is a fundamental contributor to the replication crisis: original studies published because they reached statistical significance over-select on noise-inflated effect estimates; replications find smaller effects even when the true effect is real
This sourceGelman-Carlin extending error-rate concepts to effect-size estimation sign and magnitude errors.
- T4 — Name: RTM in Replication and Winner's-Curse Contexts. RTM is a fundamental contributor to the replication crisis: original studies published because they reached statistical significance over-select on noise-inflated effect estimates; replications find smaller effects even when the true effect is real
- Statistical Power
This sourceGelman-Carlin extending error-rate concepts to effect-size estimation sign and magnitude errors.
- Type I & Type II Errors
This sourceGelman-Carlin extending error-rate concepts to effect-size estimation sign and magnitude errors.
Verification¶
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