Bioequivalence and Bioavailability Forum

Dear 0521,

❝ Dear Helmut Schütz,

Not interested in other opinions?

❝ I read the "The Use Of Non-Parametric Methods In The Statistical Analysis" document（PMID: 4556704）

Good start!

❝ 1. Determine if the P value of the sequence is greater than 0.05,

It depends on the significance level you've chosen (p). WNL cannot do that for you.
no sequence effect (or drug residual effect) in WNL terminology.

❝ 2. If the P value of the sequence is less than 0.05, the test of "Treatment" cannot be performed.

No treatment effect given no sequence effect in WNL terminology.
I would follow the text of the article you referred:
Finally, it is appropriate to note here that if the residual effects cannot be deleted from the model, then the test procedures described in section 3.2 and 3.3 are no longer valid
Corresponding sequence test (unequal carry-over) in ANOVA couldn't be a reason for analysis interruption. Likely unequal carryover doesn’t exist in a properly designed study (sufficiently long washout), hence false positives could happen.

❝ 3. If the P value of the sequence is greater than 0.05, it is judged whether the P value of the treatment is greater than 0.05.

❝ 4. If the P value of the Treatment is greater than the equivalent, otherwise it is not equivalent.

Significant != not Equivalent and vice versa! That's why we are using confidence intervals, not p-values in our BE decisions.

❝ 5. If the P value of the sequence and the P value of the Period are both greater than 0.05, a sign test can be used instead of the rank sum test used in the above steps.

You omit
3.3 Testing the equality of period effects when residual effects are absent
3.4 Testing the equality of direct effects and residual effects simultaneous ([no period effect given no sequence effect] and [no treatment and no sequence effect] in WNL terminology)
Yes, it could, but WNL does the trick with 3.4:
Since the bivariate Wilcoxon test requires only an ordinal scale for ranking across subjects, it should be used instead of the sign test for general situations in which residual and/or period effects are unequal and within subject linear functions are invalid.

Using the p-values from the Effects sheet is the same as using p-values from ANOVA: good exploratory analysis without any credible conclusions regarding bioequivalence.
It is better to compare CIs to some reference limits as Helmut noted here.