Dr Mircea Zloteanu 🌺🌞🍃#statstab #532 Fractional Bayes Factors for Model Comparison Free - O'Hagan (1995)
Thoughts: Use a fraction of the data to convert an improper prior into a minimally informative prior.
#statstab #529 How Do I Know What My Theory Predicts?
Thoughts: I'd like to see more researchers adopt Dienes' framework and way of thinking about research.
#bayesian #bayesfactor #evidence #epistemology #research #tutorial
#statstab #514 A puzzle of proportions
Thoughts: "Two popular Bayesian tests can yield dramatically different conclusions"
Model specification is important.
#statstab #486 Testing Bayesian Informative Hypotheses in Five Steps With JASP and R {bain}
Thoughts: The BAIN module let's you go beyond "effect vs no effect" by specifying contrasts (hyp) & obtaining fractional BFs.
#bain #jasp #bayesfactor #bayesian #rstats #r #hypothesis #nhbt #BF #methods #tutorial #guide
https://share.google/cTDvBO7SQM9CpNqlU
#statstab #467 Hypothesis testing, model selection, model comparison some thoughts
Thoughts: An excellent (but too short) discussion on bayesian inference.
#bayesian #bayesfactor #modelselection #inference #NBHT #BF #ROPE #primer
Hypothesis testing, model selection, model comparison - some thoughts
EDIT: This was an attempt to write guidance. It turns out I stepped quite far from my depth and the text sounded much more conclusive than it should. I think it is correct to currently just classify it as “some thoughts” rather than a guidance. I still think it is useful to have a place to list possible approaches, but the text definitely needs more work. Sorry for the confusion. Coming from classical statistics background Stan users often want to be able to test some sort of null hypothesis. S...
#statstab #453 {Bayes Power}
A General Application of Power and Sample Size Calculation for the Bayes Factors
Thoughts: Blending frequentist notions of power with bayes hypothesis testing.
#poweranalysis #bayesian #bayesfactor #errorrate #rstats #nhbt
#statstab #443 Dienes Bayes factor calculator
Thoughts: Dienes presents a different way to compute BFs using the sample data. But, this can be seen as an acceptable double-dipping.
#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 – 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, 689–701. (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.