http://researchrundowns.wordpress.com/quantitative-methods/effect-size/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444174/
http://www.wilderdom.com/research/effectsizes.html
http://www.jsams.org/article/S1440-2440(16)30219-5/fulltext
http://www.clinpsy.org.uk/forum/viewtopic.php?t=9633
t-test reports statistical significance associated with a p value – But says nothing about practical significance.
If standard deviations are small enough (especially in repeated measures design), there may be a significant difference in means, but are not large enough for practical usefulness.
Omega squared and effect size are methods to determine the usefulness of the mean difference.
Omega squared – estimate of the percentage of the total variance that is explained by the independent variable.
Effect size – estimated by the ratio of the mean difference of the groups divided by the standard deviation of the control group or pooled variance of the treatment group
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