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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 |
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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 |
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author | Aoki, Satoshi |
author_facet | Aoki, Satoshi |
author_sort | Aoki, Satoshi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7002853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70028532020-02-12 Effect sizes of the differences between means without assuming variance equality and between a mean and a constant Aoki, Satoshi Heliyon Article 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. Elsevier 2020-01-27 /pmc/articles/PMC7002853/ /pubmed/32051873 http://dx.doi.org/10.1016/j.heliyon.2020.e03306 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Aoki, Satoshi Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title | Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title_full | Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title_fullStr | Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title_full_unstemmed | Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title_short | Effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
title_sort | effect sizes of the differences between means without assuming variance equality and between a mean and a constant |
topic | Article |
url | 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 |
work_keys_str_mv | AT aokisatoshi effectsizesofthedifferencesbetweenmeanswithoutassumingvarianceequalityandbetweenameanandaconstant |