Dr Mircea Zloteanu πΊππ#statstab #531 Effect Size Calculator [Campbell]
Thoughts: A nice place for quick formulas for variance and effect sizes of various designs and data types.
#metaanalysis #effectsize #CohenD #calculator #Variance #Eta #effects
#statstab #512 Standardised mean difference estimators {shinyapp}
Thoughts: Calculating the correct SMD can be challenging, and most software are quite bad at it. Use this shiny app instead!
#statstab #502 Calculate between subjects Cohen's d from frequencies {effectsize}
Thoughts: May come in handy one day, but I'm dubious as to the inference here.
#frequency #cohend #effectsize #rstats #effectsize #shiny #r
#statstab #493 What denominator does the Cohen's d use on JASP??
Thoughts: A thread spanning years, where people figure out the many ways to compute Cohen's d. This stuff needs better labels.
#effectsize #cohend #design #japs #r
https://forum.cogsci.nl/discussion/3013/what-denominator-does-the-cohens-d-use-on-jasp
#statstab #479 Uncertainty limits the use of power analysis
Thoughts: Frequentists avoiding uncertainty is never good.
#poweranalysis #error #uncertainty #simulation #cohend #effectsize
https://www.researchgate.net/publication/361158443_Uncertainty_limits_the_use_of_power_analysis
#statstab #402 On Bayes factors for hypothesis tests {emBayes Factor}
Thoughts: On bsky there were renewed debates about BFs. This paper provides "better" priors (mixture t centred on the ES). Also some p-value BFs
#bayesian #bayesfactor #priors #cohend
https://link.springer.com/article/10.3758/s13423-024-02612-2
On Bayes factors for hypothesis tests - Psychonomic Bulletin & Review
We develop alternative families of Bayes factors for use in hypothesis tests as alternatives to the popular default Bayes factors. The alternative Bayes factors are derived for the statistical analyses most commonly used in psychological research β one-sample and two-sample t tests, regression, and ANOVA analyses. They possess the same desirable theoretical and practical properties as the default Bayes factors and satisfy additional theoretical desiderata while mitigating against two features of the default priors that we consider implausible. They can be conveniently computed via an R package that we provide. Furthermore, hypothesis tests based on Bayes factors and those based on significance tests are juxtaposed. This discussion leads to the insight that default Bayes factors as well as the alternative Bayes factors are equivalent to test-statistic-based Bayes factors as proposed by Johnson. Journal of the Royal Statistical Society Series B: Statistical Methodology, 67, 689β701. (2005). We highlight test-statistic-based Bayes factors as a general approach to Bayes-factor computation that is applicable to many hypothesis-testing problems for which an effect-size measure has been proposed and for which test power can be computed.
#statstab #396 If researchers find Cohenβs d = 8, no they didnβt
Thoughts: Sometimes an effect is so impressive that its unbelievable.
#effectsize #cohend #QRPs #sesoi
https://mmmdata.io/posts/2025/07/if-researchers-find-cohens-d-8-no-they-didnt/
#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 Cohenβs d for Measurement Error (A Method!)
Thoughts: Scale reliability can be incorporated into effect size computation (i.e., remove attenuation)