Please forgive me if this has been discussed before; I did search and could not find it.

When conducting a set of pairwise comparisons (e.g., after finding a significant main effect), one has the choice of using an error-term that is based on all of the data (which will, therefore, be the same for all of the pairs) or one that is based on only the data that are being compared (which will [almost always] differ between pairs). When one uses a common error-term for all pairs, Q-based methods of correcting for multiple comparisons become available, such as Tukey's HSD. When one uses unique error-terms, one can only [easily] use p-value correction, such as Bonferroni.

JAMOVI uses the common error-term approach for both between- and within-subject effects. In contrast, for example, SPSS uses a common error-term for between-subject factors and unique error-terms for within-subject factors.

Without getting into a debate on which approach is better for within-subject designs, is there any plan to add the option of using unique error-terms for pairwise comparisons involving a repeated measure? Relatedly, is there any plan to add Dunn-Sidak correction as an option?

Thanks.