2004
DOI: 10.1037/1082-989x.9.4.426
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The Power of Statistical Tests for Moderators in Meta-Analysis.

Abstract: Calculation of the statistical power of statistical tests is important in planning and interpreting the results of research studies, including meta-analyses. It is particularly important in moderator analyses in meta-analysis, which are often used as sensitivity analyses to rule out moderator effects but also may have low statistical power. This article describes how to compute statistical power of both fixed- and mixed-effects moderator tests in meta-analysis that are analogous to the analysis of variance and… Show more

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Cited by 567 publications
(469 citation statements)
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“…This did not appear to be simply function of limited statistical power because, based on the procedures described by Hedges and Pigott (2004) for mixed-effects regression models, we had a power of .54 to detect a small effect (r = .10), a power of .89 to detect a medium effect (r = .30), and a power of greater than .99 to detect a large effect (r = .50). These calculations were based on 2-tailed inferential tests and an assumed variance of .1, which was a conservative value that exceeded all observed error variances.…”
Section: Moderators Of Obesity Prevention Effectsmentioning
confidence: 99%
“…This did not appear to be simply function of limited statistical power because, based on the procedures described by Hedges and Pigott (2004) for mixed-effects regression models, we had a power of .54 to detect a small effect (r = .10), a power of .89 to detect a medium effect (r = .30), and a power of greater than .99 to detect a large effect (r = .50). These calculations were based on 2-tailed inferential tests and an assumed variance of .1, which was a conservative value that exceeded all observed error variances.…”
Section: Moderators Of Obesity Prevention Effectsmentioning
confidence: 99%
“…Fourth, the quality of included studies was variable (e.g., medication was allowed alongside psychotherapy in 23 studies). Although the results of subanalyses to examine the moderating effect of use of treatment manual, treatment fidelity, and medication use showed that these variables (pharmacotherapy use, treatment length, mean number of sessions, year of publication) did not account for a significant proportion of variance in treatment effects, power for testing moderators is often low (Borenstien et al, 2009;Hedges & Pigott, 2004). Additional points for consideration on methodological study quality such as blinding of observer-rated outcomes, reporting of intention to treat analyses, and the reliability of random allocation procedure may, however, have had an influence on treatment effects.…”
Section: Critical Analysismentioning
confidence: 99%
“…32 In addition, moderator analyses have only limited power with a small set of studies. 40,41 This latter limitation is particularly noteworthy given the substantial heterogeneity that was found in the elderly studies. Our results revealed that 68 percent of the variance in effect sizes across the elderly studies was attributable to systematic differences.…”
Section: Effectiveness Of Active Videogamesmentioning
confidence: 96%
“…38,39 Significant prediction indicates that the effect sizes vary in a linear manner with the continuous moderator. It should be noted, however, that the statistical power of moderator analyses in meta-analysis is not always high 40 and that a large number of studies is generally needed to detect effects. 41 Given that research about active videogames is still in its infancy, so that not many published studies exist, 9,16 the results of these analyses should be considered with caution.…”
Section: Effectiveness Of Active Videogamesmentioning
confidence: 99%