Bioequivalence and Bioavailability Forum

Dear RB!

❝ I have a 3 period, 2 treatment crossover (TRR, RTT) design and used the following code (as per FDA guidance) to analyse the data:

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❝ FDA 2001 Apendix E

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❝ The above analysis resulted in the following note in the SAS log: "Estimated G matrix not positive definite" suggesting that "one or more variance components on the RANDOM statement is/are estimated to be zero and could/should be removed from the model."

Yes, old story. SAS complains about an over-specified model (T is not repeated) and gives a variance for T. See this thread.

❝ My colleague is suggesting I switch the covariance structure to VC however I'm concerned that this negates the REPEATED statement and is questionable in a 3x2 design. What is your opinion on this point?

Agree.

❝ I used the CSH structure but, as expected, encountered the same notes in the log.

Yep.

❝ Looking through the covariance structures, Compound Symmetry (CS) looks more appropriate as it accounts for correlation & assumes it is constant regardless of the lag between pairs of repeated measurements (sounds OK given the study design).

Interesting idea. At least you don’t get a warning any more.
Tried it with EMA’s example data set II (TRR|RTR|RRT) and got (Phoenix 6.2 = poor man’s SAS):

                         90% CI         CVWR   CVWT
EMA's Model A         97.32  107.46
EMA’s Model B         97.32  107.46
EMA’s crippled model       NA          11.20   NA
FDA FA0(2)            97.05  107.76    11.55   8.65 Warning (SAS: CVWT=3.87)
FDA CSH               not estimable     8.26   7.15 Warning
FDA CS                97.05  107.76    11.55  18.67 no Warning!

• Pro: CV_WR is identical to FA0(2) and you don’t get a warning with CS.
  
• Con: That’s not what FDA expects you to do: FA0(2) or possibly [sic!] CSH. I have strong doubts whether the value of CV_WT makes any sense.