#statstab #478 Equivalence Tests {marginaleffects}
Thoughts: Often you want to test "no difference" in more complex models than many packages or software permit.
With a few lines of code you can do that for most models.
#Equivalence #noeffect #rstats #TOST #EQ #NHST #hypothesistesting
https://marginaleffects.com/chapters/predictions.html#sec-predictions_visualization
5 Predictions – Model to Meaning
#statstab #327 Effect Sizes for Equivalence Testing: Incorporating the Equivalence Interval
Thoughts: Not sure what value this approach has yet, but sharing for feedback.
#equivalencetests #sesoi #nhst #noeffect #nonsignificant #practicalsignificance
https://osf.io/preprints/psyarxiv/5buz9_v1

Ronan Courty – Synesthesia
In a modern musical and artistic landscape, it becomes difficult to stay unique, fresh, and innovative. Artists and bands do their best to craft and unleash their pieces of work in order to break t…
Thoughts Words Action#statstab #238 Bridging null hypothesis testing and estimation
Thoughts: An overview of the ways you can claim "no effect" under a bayesian framework.
#bayesian #bayesfactors #nullresults #noeffect #equivalencetests #equivalence #jasp #r
https://osf.io/preprints/psyarxiv/c7b45
#statstab #232 Bayesian Interval-Null Testing
Thoughts: @JASPStats has a module for Equivalence Tests that include Bayesian Overlapping and Non-Overlapping Hypothesis Testing.
#equivalencetests #bayesfactors #jasp #noeffect #bayes
https://jasp-stats.org/2020/06/02/frequentist-and-bayesian-equivalence-testing-in-jasp/

Frequentist and Bayesian Equivalence Testing in JASP - JASP - Free and User-Friendly Statistical Software
This post demonstrates the Equivalence Testing Module, new in JASP 0.12. In traditional hypothesis testing, both frequentist and Bayesian, the null hypothesis is often specified as a point (i.e., there is no effect whatsoever in the population). Consequently, in very… Continue reading →
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