Bioequivalence and Bioavailability Forum

Dear All!

Talking a little bit with myself for psycho-hygiene.

After walking a while on the bear way, sun was shining , all was good, suddenly I came into a dark wood, to a big dark hole in which the three-headed hydra resides.
She was horrible looking, totally out of balance and equipped with dreadful mixed (un)expected means and (non)integer degrees of freedom .

Quick I employed the famous bogus RANDOM statement of Proc GLM, which I was preventively armed with during this adventure, to inspect the expected mean squares of the data and to perform the 'appropriate' F-tests for banishing that beast arosen from the depth of moria .
(Unfortunately the mightier Proc Mixed was prohibited to me by the custodians of the bear-way on EMA territory.)

Here the result: evaluation of example 4.2 from Patterson/Jones, a dataset from a 3-period-2-sequence replicate crossover design with the sequences RTT (39 subjects) and TRR (35 subjects), without missing data.
                       Classical Proc GLM, Cmax
                             The GLM Procedure

Source                Type III Expected Mean Square

formula            Var(Error) + Q(formula)

period             Var(Error) + Q(period)

sequence           Var(Error) + 2.6667 Var(subject(sequence)) + Q(sequence)

subject(sequence)  Var(Error) + 3 Var(subject(sequence))
*-------------------------------------------------------------------------
                             The GLM Procedure
         Tests of Hypotheses for Mixed Model Analysis of Variance

Dependent Variable: ln_cmax

 Source                 DF   Type III SS   Mean Square  F Value  Pr > F

 formula                 1      0.829991      0.829991     4.89  0.0286
 period                  2      0.331868      0.165934     0.98  0.3786
 subject(sequence)      72    190.981556      2.652522    15.63  <.0001

 Error: MS(Error)      145     24.606438      0.169700


 Source                 DF   Type III SS   Mean Square  F Value  Pr > F

 sequence                1      2.490853      2.490853     1.05  0.3093

 Error              73.154    173.861309      2.376652
 Error: 0.8889*MS(subject(sequence)) + 0.1111*MS(Error)

After I had survived this beastly monster due to my extra-power-to-know I had questions:

• Somebody out there which had similar "Close Encounters of the Third Kind"?
  
• Or was this only Morgan le Fay confusing me while looking through my rose-tinted ®^SAS® glasses?
  
• Can we also survive equipped with other arms not so expensive (especially R)?

BTW: Non-integer df due to Satterthwait approximation due to mixture of MS'ses. Again the result of defining subject nested within sequence as the expatriated random effect.