#statstab #364 Distribution of Cohen's d, p-values, and power curves for an independent two-tailed t-test
Thoughts: Useful for explaining why we use 5% alpha and what power does to p-values.
#statstab #364 Distribution of Cohen's d, p-values, and power curves for an independent two-tailed t-test
Thoughts: Useful for explaining why we use 5% alpha and what power does to p-values.
#statstab #294 So You Think You Can Graph - effectiveness of presenting the magnitude of an effect
Thoughts: Competition in the many ways to display effect magnitude. Some cool ideas.
#dataviz #stats #effectsize #effects #plots #figures #cohend
https://amplab.colostate.edu/SYTYCG_S1/SYTYCG_Season1_Results.html
#statstab #281 Correcting Cohen’s d for Measurement Error (A Method!)
Thoughts: Scale reliability can be incorporated into effect size computation (i.e., remove attenuation)
#statstab #260 Effect size measures in a two-independent-samples case with nonnormal and nonhomogeneous data
Thoughts: "A_w and d_r were generally robust to these violations"
#robust #effectsize #ttest #2groups #metaanalysis #assumptions #ttest #cohend
#statstab #226 Standardization and other approaches to meta-analyze differences in means
Thoughts: "standardization after meta-analysis...can be used to assess magnitudes of a meta-analyzed mean effect"
#statstab #153 Difference between Cohen's d and beta coefficient in a standardized regression
Thoughts: This relationship bw (beta) and (d) may be useful in some reporting edge cases, like #metaanalysis