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[Bayesian rm-ANOVA] Model averaged posterior distribution

Hi,

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.

Comments

  • Hi OCOD,

    Good point. I will pass this on to Don van den Bergh, who did most of the recent work on this. On a side note, we are really close to having R syntax support, which should hopefully make everything clearer than it is now. Seems we are two version away from this.

    Cheers,

    E.J.

  • Right that makes sense. Thank you, and I look forward to these additions. Great piece of software overall!

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