Eta values were calculated to assess effect sizes.
Moreover, this is helpful statistically because classifications reduce the dimensionality of the data thus permitting one to assess effect sizes between classes rather than assessing effects associated with each potential combination of pollutant levels.
Post hoc analyses assessed interaction between sex or age and treatment and assessed effect sizes for Swanson, Kotkin, Agler, M-Flynn, and Pelham (SKAMP) and Permanent Product Measure of Performance (PERMP) scales and ADHD Rating Scale IV measures.
We estimated several models with individual, or a combination of, factors to assess their effect size and significance given some level of collinearity between fitness and efflux-type (Fig. 3, Supplementary Fig. 5a r).
We conducted two meta-analyses in order to assess the effect size of the relationship between predictions and emotions.
We therefore used sequential GLM models to assess the effect size of each predictor in influencing price.
The trend towards significance provides some evidence for this interpretation, but future studies are required to assess the effect size and the robustness of this finding.
Prevalence rates were compared using the chi-square test, and prevalence ratios were estimated in order to assess the effect size of differences.
Strictly standardized mean difference (SSMD) was first proposed to assess siRNA effect size, and modified later to balance false-negatives and false-positives in hit selection [ 12, 13].
