Thank you for the update Ravi. I really appreciate it. I am by no means a stats expert, but if I understand correctly using the pooled SE increases the power of the test, correct? Below I left a DropBox link to a powerpoint file with all the screenshots of different post hoc tests from both Statistica and Jamovi. It requires a little explanation. Apologies for the long comment. I really love what you guys are doing and really hope this takes off. The different levels in Statistica are labeled by number: 1 is fall, 2 is none, 3 is rise. Reading the tables in Statistica is like a correlation matrix table of lining up rows with columns. Looking at the comparisons in sound Statistica's results with Tukey's and Bonferroni has 1 vs 2 (fall vs none) as non-significant, whereas in Jamovi all comparisons are significant (in this example the degrees of freedom are the same between the two programs at 62). Still, there is quite a large difference in the one comparison between the two. The ANOVA result revealed a significant main effect for distance, so I show that here as well. The images showing the bonferroni and tukey tests in Statistica show no significant effects among different levels of distance, whereas the Jamovi result show one significant result between 5 vs 10cm (which would be just cells 1 vs 3 in Statistica table). Here, too, the degrees of freedom are the same at 62. But there is something else strange (or just a coincidence) here. In the bonferroni table from Statistica it has a p value of .3678 for the comparison 1 vs 3 cells (or 5 vs 10cm). That is pretty much the exact p value for the bonferroni result in Jamovi but between 5 vs 7cm. Similarly, with the Tukey's test in Statistica the p value between 1 vs 3 (5 vs 10cm) is .268 is pretty much the same as the Jamovi tukey's test for comparisons between 5vs7cm (I hope this is not getting too confusing). I have seen other similar p values but for different comparisons between the two stat programs and wondered if there might be an error in populating the results table. For the comparisons for Direction * Sound I only show the tukey results from Statistica. Direction 1 is down, 2 is up, sound 1 is fall, sound 2 is none, and sound 3 is rise. You can see that Statistica reports only one df and it is 62. The Jamovi table shows different degrees of freedoms for the different comparisons. Again I am no stats expert but it looks weird that they are not truly unique if each comparison has an adjusted dfs for that comparison. I can't work out a discernible pattern. Despite a lot of agreement with lots of significant comparisons, there is still some big discrepancies - for instance comparing up-fall with up-none: in Statistica the p value approaches significance with a p value of 0.078 (in the table that is row 4 vs column 5). Depending on one's philosophy on statistically reporting, one can say that there is a marginal effect and may even tell students to keep collecting a few more subjects. Compare that one result on Jamovi and the p value is 0.2. Not very marginal at all and quite different. Thanks for all your help and work on this!

https://www.dropbox.com/s/8azl5q3yalvbm ... .pptx?dl=0