Bioequivalence and Bioavailability Forum

Hello arl_stat,

❝ I am planning to perform Anova including Treatment*Batch first. Further if there is no significant Treatment*Batch effect then to again perform Anova excluding Treatment*Batch effect. Correct me if I am wrong. Also it would be appreciable if can someone explain me these Anova Factors(i.e. Batch, Sequence, treatment, batch*treatment and Period(batch), and Subject(sequence*Batch) )

Your proposal is perhaps not completely in line with model reduction habits in the pharmaceutical industry. Some companies might use Akaike or Schwarz info criteria to select factors that go into the trash can. Anyways, no personal objection from me.
Explanation of Anova factors...? I assume you mean the interactions or nestings? Let's take Subject(Sequence*batch); in this case imagine you have

-subject 1,2,3,4 in batch 1 of sequence 1.
-subject 1,2,3,4 in batch 2 of sequence 2.
-subject 1,2,3,4 in batch 1 of sequence 2.
-subject 1,2,3,4 in batch 2 of sequence 1.
All these subjects are different subjects, so they are just coded in a dumb way. It des not make sense to ask what the fixed effect of subject 3 is if you don't specify which of the four subject 3's you think of. In such a situation it makes sense to apply Subject(batch * sequence). The unreduced model matrix will have 16 columns for the fixed treatment levels for that (4+4+4+4 as indicated above) - you will then loose a couple of them due to the df redundancy. How many depends on whether you have requested an intercept and which factors are preceding Subject (batch * sequence) in your specification.