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Very strong evidence in Post-Hoc but no main effect

Dear all,

I conducted a three-way repeated measures ANOVA (2x2x4) and did not observe a main effect for one of the factors, which is named "region of interest" (ROI). However, upon running a post-hoc test, I discovered strong evidence indicating a significant difference between the two levels of this factor (BF10 > 100). Any insights or ideas as to why this might be the case would be greatly appreciated.

Thank you for your input.

Best regards,

María Paula


  • Could there be assumption-violations? It's difficult to tell what might be going on without seeing the actual data.


  • Yes the data would be good, but screenshots of the relevant tables would be good too. Did you use a recent version of JASP? We updated the model specification a year ago, see for instance

  • I did use the recent version of JASP and the specifications in the 2022 paper. I also included the comparison of only matched models that Sebastian suggested as specified in the paper of 2020. Based on the Q-Q plots I believe there was not an assumption that has been violated (correct me if I am wrong).

    This is the analysis of the effects:

    Post hoc

    Q-Q plots:

    Am I missing something important? Please let me know, and thank you so much for your quick replies.



  • Could there be any rows with missing data that are excluded from the ANOVA but (incorrectly) included in the post hoc test?


  • There are not missing values in the data, from what I checked just now. As far as I know, it is not possible to check or correct some assumptions (like non-sphericity) in the Bayesian ANOVA features in JASP as it is now. Maybe there will lie the issue? What other option may have caused this?

  • I wonder, what is the result of a frequentist repeated measures ANOVA on the same data? Does it still produce an incongruence between main effect and post hoc?


  • Do you have a raincloud plot of the data, showing the effect?

  • This is the rain cloud plots of ROI.

    And regarding the frequentists ANOVA: with corrections for not met assumptions:

    The frequentist says it is not significant

  • This is a little puzzling, because the uncorrected BF ought to be just a t-test BF, and that particular t-value would not give such a huge BF (but something anecdotal in favor of H0). I've asked the team.

  • Thank you so much for your time and caution in this matter! I will be looking forward to your response.

    Best wishes,


  • So suppose you take all of the "visual" data points, and compare it to all of the "motor" data points, collapsing across all other factors -- for that t-test, what is t and n?

  • I did it like you mentioned:

    For the frequentist analysis I got a significant p-value and for the BF I got a similar one to the post-hoc test value.

    The n is 152.

  • Ah, so this is t=-4.747, and that matches with the BF10. So the problem, it seems, is that in our Bayesian post-hoc test we average across all the other factors and levels, and this is not what the frequentist test does. I'll see whether the team has something to add.

  • Alright. Once again, thank you so much for your prompt responses! :)

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