I am trying to work out the most appropriate way to adjust for multiple comparisons.
I have 20 biomarkers which have been measured at 4 timepoints (baseline & three unevenly spaced follow-ups). I will analyse each biomarker separately using either anova measuring changes from baseline at each time point (3 tests), or used mixed-models to assess changes over time (1 test).
If I use the Bonferroni correction, my cut-off for significance is very low & I lose a lot of power. Would I be correct in saying for the first case (comparison at each time point), the adjusted p-value threshold would be 0.05/(20*3) = 0.0008 & for the second example (over time), the threshold would be 0.05/20 = 0.0025?
Is there a more suitable correction method that would help me retain power someone could recommend?