Contrasts and Correlations in Effect-Size Estimation
Bibliographic Data
| ID | 23319142 |
|---|---|
| Authors | Ralph L Rosnow (Temple University, corresponding author), Robert Rosenthal (Department of Psychology, University of California, Riverside), Donald B Rubin (0000-0001-7127-9262, Harvard University) |
| Year | 2000 |
| Volume | 11 |
| Issue | 6 |
| Pages | 446-453 |
| Publication date | 2000-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychological Science (JOURNAL) |
| Journal identifiers | ISSN: 0956-7976 • E-ISSN: 1467-9280 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1111/1467-9280.00287 |
| PMID | 11202488 |
| OpenAlex | W2031256578 |
| Language | EN |
| Citations received | 66 |
| References cited | 20 |
This article describes procedures for presenting standardized measures of effect size when contrasts are used to ask focused questions of data. The simplest contrasts consist of comparisons of two samples (e.g., based on the independent t statistic). Useful effect-size indices in this situation are members of the g family (e.g., Hedges's g and Cohen's d) and the Pearson r. We review expressions for calculating these measures and for transforming them back and forth, and describe how to adjust formulas for obtaining g or d from t, or r from g, when the sample sizes are unequal. The real-life implications of d or g calculated from t become problematic when there are more than two groups, but the correlational approach is adaptable and interpretable, although more complex than in the case of two groups. We describe a family of four conceptually related correlation indices: the alerting correlation, the contrast correlation, the effect-size correlation, and the BESD (binomial effect-size display) correlation. These last three correlations are identical in the simple setting of only two groups, but differ when there are more than two groups.
Binomial (polynomial) · Contrast (vision) · Correlation · Pearson product-moment correlation coefficient · Sample size determination · Statistic · Statistics · Artificial Intelligence · Computer Science · Data Visualization and Analytics · Mathematics · Meta-analysis and systematic reviews · Psychology · Sensory Analysis and Statistical Methods · Social Psychology
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| Unique citing works | 66 |
|---|---|
| Citations per year | 2,75 |
| Citation span | 2002 - 2026 (25) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 60 |