#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)

#measurementerror #effectsize #cohend #reliability #scales

http://rpubs.com/JLLJ/RPBD

#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

https://link.springer.com/article/10.3758/s13428-015-0667-z

#psychology #statistics #research #abtesting

#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"

#metaanalysis #effectsize #cohend #clinical

https://onlinelibrary.wiley.com/doi/10.1002/sim.10114?af=R

#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

#cohend #regression #effectsize

https://stats.stackexchange.com/questions/472810/difference-between-cohens-d-and-beta-coefficient-in-a-standardized-regression-m