I have seen some guides on how to craft your language when reporting statistical results (e.g., Smith (2020) https://doi.org/10.1007/s12237-019-00679-y) but does anyone know how to report multiple comparisons? Especially if you have numerous comparisons to talk about (ie > 10), it would be impractical to use boxplots.
All current approaches to handling multiple comparisons focus on (read: are equivalent to) using significance tests and modifying thresholds based on ranked unadjusted p-value, the overall number of tests, and either the prespecified family-wise error rate or the number of false discoveries, etc. It seems necessary to invoke null hypothesis significance testing to some degree to handle multiplicity.
The chief complaint against a p-value is that it is not quantitatively useful in its own right. To summarize findings, (and 10 comparisons is not a lot), you can use a simple forest plot with 95% CIs. These are powerful visual tools and convey a large quantity of information in a readily digestible format, Standardize the estimated effect then show significance in terms of the magnitude and precision of effect according to the ranked test statistics for each comparison.