Interpretation of oppositely directed effects
I'm currently struggling with the following situation: Im conducting two Baysian repeated measures t-Tests. The two conditions I want to compare are the same in both analyses, but for two different DV. In both cases I'm trying to quantify the evidence for the hypothesis that Measure 1> Measure 2.
Test 1 shows evidence for the hypothesis with BF+0=10
Test 2 shows very strong evidence against it with BF+0=0.0001
Can these results be combined to conclude that there is overall evidence against the hypothesis?
Can both BF be combined to quantify the total evidence, i.e. in this case as something like .001?
Do I have to perform a combined test that features both DV as a compound variable, or is none of this valid and both results have to be regarded as strictly separate?
Thank's a lot!