2014
DOI: 10.4324/9781315773155
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Statistical Power Analysis

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Cited by 130 publications
(35 citation statements)
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“…[12][13][14][15]17,24 However, the methods for comparing skill were not optimal resulting in a lack of power in the significance test and an underestimation of the impact of initialisation. The power of a significance test is defined as the probability that it will correctly detect a real signal, and depends largely on the size of the signal being tested, [40][41][42] referred to as the effect size. Previous studies have assessed simple differences (or ratios) of skill, but this approach does not maximise the effect size when part of the skill is common to both sets of forecasts.…”
Section: Resultsmentioning
confidence: 99%
“…[12][13][14][15]17,24 However, the methods for comparing skill were not optimal resulting in a lack of power in the significance test and an underestimation of the impact of initialisation. The power of a significance test is defined as the probability that it will correctly detect a real signal, and depends largely on the size of the signal being tested, [40][41][42] referred to as the effect size. Previous studies have assessed simple differences (or ratios) of skill, but this approach does not maximise the effect size when part of the skill is common to both sets of forecasts.…”
Section: Resultsmentioning
confidence: 99%
“…Bonferroni adjustments were made for each ANCOVA or MANCOVA but no overall experiment-wise adjustments were made. By convention, partial eta squared effect sizes are interpreted as: .01~small, .06~medium, and .14~large (Murphy & Myors, 2004).…”
Section: Discussionmentioning
confidence: 99%
“…* and † = p < .05 for a given pairwise comparison. By convention, partial eta squared effect sizes are interpreted as: .01~small, .06~medium, and .14~large (Murphy & Myors, 2004). Bonferroni adjustments were made for each ANCOVA or MANCOVA but no overall experiment-wise adjustments were made.…”
Section: Aimmentioning
confidence: 99%
“…To determine the necessary sample size for this study, power analyses for the design were calculated a priori using G * Power 3.1 (Buchner, Erdfelder, & Faul, 1997). Based on Myors & Wolach's (2014) recommended power statistic of 0.80, an analysis of variance (ANOVA) with fixed effects, omnibus, one-way was conducted. Given an effect size of 0.14 (low effect size), alpha level of 0.05, power statistic of .80, seven groups, and three response variables, the study's sample size of 702 possesses sufficient power to determine whether there is a relationship between the independent variable and outcome measures if such a relationship exists and is robust enough to detect.…”
Section: Data Analysesmentioning
confidence: 99%