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Effect sizes of the differences between means without assuming variance equality and between a mean and a constant
Effect sizes of the difference, or standardized mean differences, are widely used for meta-analysis or power-analysis. However, common effect sizes of the difference such as Cohen's d or Hedges' d assume variance equality that is fragile and is often violated in practical applications. Bas...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7002853/ https://www.ncbi.nlm.nih.gov/pubmed/32051873 http://dx.doi.org/10.1016/j.heliyon.2020.e03306 |
Sumario: | Effect sizes of the difference, or standardized mean differences, are widely used for meta-analysis or power-analysis. However, common effect sizes of the difference such as Cohen's d or Hedges' d assume variance equality that is fragile and is often violated in practical applications. Based on Welch's t tests, we defined a new effect size of the difference between means, which did not assume variance equality, thereby providing a more accurate value for data with unequal variance. In addition, we presented the unbiased estimator of an effect size of the difference between a mean and a known constant. An R package is also provided to compute these effect sizes with their variance and confidence interval. |
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