Strange behavior with Bayesian RM-ANOVA
I'm using JASP for a while and I think is a really great tool.
I ran both classical and Bayesian 2 ways - RM -ANOVA. by using the the classical analysis I got main effect to one variable ("cong") and I didn't get main effect to the second variable (go_nogo). In addition, I also didn't get interaction.
However, when I ran the Bayesian analysis I got evidence to the existing of the main effect to the second variable go_nogo).
As far as I understand Bayesian statistic, the pattern should be the same. I understand that it possible to find that by using Bayesian analysis effect will disappear, but I'm not really sure how it possible to find different effects.
For being sure that I didn't miss anything, I ran more 2 tests:
- one-way (both classical and Bayesian) RM-ANOVA to the 'cong' variable.
- paired samples t-test (both classical and Bayesian) for the 'go_nogo' task.
The results for these 2 tests were same (at least in the pattern):
There was a different between the levels of the 'cong' variable (F=22.16, p<.001, BF10=21,142.844) and no different found in the go_nogo variable(t=1.385, p=.184, BF01 = .539).
However, the results for the two-way ANOVA (as I described before) in the Bayesian analysis:
is different from the classical one:
In addition, the "behaviour" of the Bayesian analysis is also different from the results given by the analysis of each variable separately (as given from the one-way ANOVA and from the paired samples t-test)
I can't find any mistake in my steps and I'll really appreciate your comments.
In any case, the jasp file (that includes the latest analysis) is attached as a zip file: https://github.com/jasp-stats/jasp-issues/files/2872991/jasp_inc_ttest_anova.zip
Thanks a lot in advance,