WinNonlin random vs. fixed model [Power / Sample Size]

posted by Helmut Homepage – Vienna, Austria, 2012-11-30 14:54 (4957 d 01:53 ago) – Posting: # 9643
Views: 11,013

Hi Krishna!

❝ After doing above correction in WinNonlin, I am observing slight increase in SE as a consequence CI is widening slightly.


Which version of WinNonlin? Did you get a “Warning 11094: Negative final variance component” in the random effects model (WinNonlin’s default)? If yes, the result is not reliable (overspecified model). Therefore results might differ – but only the fixed effects model is valid. If you didn’t get a warning and use the fixed effects model (according to EMA’s GL) the results should be identical.

❝ Also, p-value for sequence is working against 'Residual Error' as error term rater than 'Subject(sequence)' term.


I don’t know why you want to test for this effect at all. BTW, you are rather interested in Subject(Sequence), which is identical in both models. Try it with WinNonlin’s Data22 example (the famous Clayton & Leslie data set).*

❝ How this problem can be fixed and what is the reason for increment of SE ?


Don’t understand what you want to ‘fix’. Consider registering at Pharsight’s Extranet and ask there.



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