Calculating statistical power for meta-analysis using metapower
Meta-analysis is an influential evidence synthesis technique that summarizes a body of research. Though impactful, meta-analyses fundamentally depend on the literature being sufficiently large to generate meaningful conclusions. Power analysis plays an important role in determining the number of stu...
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Université d'Ottawa
2021-03-01
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Online Access: | https://www.tqmp.org/RegularArticles/vol17-1/p024/p024.pdf |
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doaj-02671afb1f884247b679fe4f8736faa52021-03-19T23:09:43ZengUniversité d'OttawaTutorials in Quantitative Methods for Psychology1913-41262021-03-01171243910.20982/tqmp.17.1.p024Calculating statistical power for meta-analysis using metapowerGriffin, Jason W.Meta-analysis is an influential evidence synthesis technique that summarizes a body of research. Though impactful, meta-analyses fundamentally depend on the literature being sufficiently large to generate meaningful conclusions. Power analysis plays an important role in determining the number of studies required to conduct a substantive meta-analysis. Despite this, power analysis is rarely conducted or reported in published meta-analyses. A significant barrier to the widespread implementation of power analysis is the lack of available and accessible software for calculating statistical power for meta-analysis. In this paper, I provide an introduction to power analysis and present a practical tutorial for calculating statistical power using the R package metapower. The main functionality includes computing statistical power for summary effect sizes, tests of homogeneity, categorical moderator analysis, and subgroup analysis. This software is free, easy-to-use, and can be integrated into a continuous work flow with other meta-analysis packages in R.https://www.tqmp.org/RegularArticles/vol17-1/p024/p024.pdfmoderator analysispower analysisstatistical softwaresystematic reviewevidence synthesisr |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Griffin, Jason W. |
spellingShingle |
Griffin, Jason W. Calculating statistical power for meta-analysis using metapower Tutorials in Quantitative Methods for Psychology moderator analysis power analysis statistical software systematic review evidence synthesis r |
author_facet |
Griffin, Jason W. |
author_sort |
Griffin, Jason W. |
title |
Calculating statistical power for meta-analysis using metapower |
title_short |
Calculating statistical power for meta-analysis using metapower |
title_full |
Calculating statistical power for meta-analysis using metapower |
title_fullStr |
Calculating statistical power for meta-analysis using metapower |
title_full_unstemmed |
Calculating statistical power for meta-analysis using metapower |
title_sort |
calculating statistical power for meta-analysis using metapower |
publisher |
Université d'Ottawa |
series |
Tutorials in Quantitative Methods for Psychology |
issn |
1913-4126 |
publishDate |
2021-03-01 |
description |
Meta-analysis is an influential evidence synthesis technique that summarizes a body of research. Though impactful, meta-analyses fundamentally depend on the literature being sufficiently large to generate meaningful conclusions. Power analysis plays an important role in determining the number of studies required to conduct a substantive meta-analysis. Despite this, power analysis is rarely conducted or reported in published meta-analyses. A significant barrier to the widespread implementation of power analysis is the lack of available and accessible software for calculating statistical power for meta-analysis. In this paper, I provide an introduction to power analysis and present a practical tutorial for calculating statistical power using the R package metapower. The main functionality includes computing statistical power for summary effect sizes, tests of homogeneity, categorical moderator analysis, and subgroup analysis. This software is free, easy-to-use, and can be integrated into a continuous work flow with other meta-analysis packages in R. |
topic |
moderator analysis power analysis statistical software systematic review evidence synthesis r |
url |
https://www.tqmp.org/RegularArticles/vol17-1/p024/p024.pdf |
work_keys_str_mv |
AT griffinjasonw calculatingstatisticalpowerformetaanalysisusingmetapower |
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