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# "flag significant comparisons" option in the PostHoc section - can we trust it?(JASP)

Hello guys,

I was wondering if after performing ANOVA in JASP, I can actually rely on the "flag significant comparisons" option in the PostHoc section or I need to manually adjust to my new adjusted p-value?

For example (image + data attached): I performed a behavioural test helping me to divide participants into 3 groups (controls, abnormal and normal). Then, I wanted to check their brain atrophy level as based on this division.

ANOVA is significant (p = 0.046), so I performed a PostHoc (I chose Bonferroni). There are 3 comparisons to make as I have 3 sub-groups of participants, so the new adjusted p-value for Bonferroni is = 0.05/3 = 0.016666 (this one is just manually calculated as I don't see it in JASP).

However, I chose the option "flag significant comparisons" and there is a Bonferroni result p = 0.048 which is indicated by JASP as significant. Still, if I make the above calculation manually where I got the new adjusted p = 0.016666, then this result of p = 0.048 should not actually be indicated as statistically significant.

Still, there is this beautiful note:"P-value adjusted for comparing for a family of 3"

So, is JASP somehow taking the new adjusted p -value and calculating it in a manner that is easy for us to understand and adjusting it to the initial alpha of 0.05 OR "the flag significant comparisons" has another meaning and we should not trust it , but unfortunately manually calculate the new adjusted p-value and make a case by case individual decisions?

Thank you and best wishes!

• The Bonferroni adjustment can either be an adjustment to the alpha that is used for deciding on statistical significance (e.g., 0.05 / 3 = 0.016666), or you can adjust the observed p-values themselves by multiplying them by the number of comparisons and then compare them to the initial alpha (e.g., 0.05).

JASP takes the latter approach (as most other statistics software do, because then you can use any alpha value), so the p-values you see are already adjusted by the Bonferroni method (hence the subscript in the column name, and the footnote in the table). So for instance, the p-value you see would be 0.048 / 3 = 0.016 unadjusted.

The flag option then puts an asterisk next to all adjusted p-values < 0.05. I hope this clarifies the issue, please let me know if you have any further questions.

Kind regards,

Johnny

• edited November 8

Thank you so much, Johnny! That was really helpful. Now, I know I can trust Jasp calculations for multiple comparisons.

kind regards and thanks again!