I am currently analyzing data for an age-related neuroscience study with a 2x2 factorial design (treatment (2 levels) x age (2 levels)) yielding 4 total groups: Young untreated, Young treated, Aged untreated, Aged treated. The hypothesis is that the two aged groups would be different, while young animals show no difference. My first thought is to perform a factorial ANOVA (test for main effect of genotype and age, as well as test for an interaction effect). However, if there is no interaction effect of the two variables, I'd still like to test that original hypothesis (i.e., compare just the aged groups and just the young groups). I've recently learned that some researchers employ planned comparisons (I've also seen it called planned contrasts) to examine differences between specific groups that were selected a priori instead of doing an ANOVA and running post-hoc tests that examine all possible comparisons.
This makes sense to me, but I've heard that scientific journals "don't like" when researchers use planned comparison, so getting published with planned comparisons would be difficult if not near impossible. On the other hand, through very cursory internet searching, I found 2 papers that seem to advocate for the use of planned comparisons since every study should have a hypothesis that predicts specific effects anyway (The papers can be found here and here).
Given all this, my question is as follows: Is it generally acceptable to do planned comparisons if there's a rational justification for it, or is this approach frowned upon by journals and peer reviewers?