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[Bayesian rm-ANOVA] Model averaged posterior distribution


I have a 2x3 within-participant dataset, that I analysed using a bayesian rm-ANOVA. I really liked the possibility of plotting model averaged posterior distribution of each factor level and their interactions, but I do not understand how they are obtained? That is, if I take my dataset and re-implement the analysis on Python or Matlab, how can they be reproduced? To be clear, getting a model average is not the problem (that's actually pretty straightforward), but getting the posterior of each level's effect size individually confuses me. I am working mainly from the paper from Rouder et al. (2012).

Thank you in advance for your input.

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