ElMag ☆ 2011-02-15 15:58 (5180 d 15:53 ago) Posting: # 6626 Views: 5,402 |
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Hello! Could you please tell me how can I find the intra-subject variability from Winnonlin? I would like you to tell me the exact steps I have to follow in order to have intra-subject variability result in the Winnonlin output. I would appreciate your prompt reply! Best regards ElMag Edit: Category changed. [Helmut] |
Helmut ★★★ ![]() ![]() Vienna, Austria, 2011-02-15 18:26 (5180 d 13:25 ago) @ ElMag Posting: # 6627 Views: 4,706 |
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Iassou ElMag! ❝ Could you please tell me how can I find the intra-subject variability from Winnonlin? I would like you to tell me the exact steps I have to follow in order to have intra-subject variability result in the Winnonlin output. In the current versions (WinNonlin5.3 and Phoenix 6.1) for a 2×2 cross-over on log-transformed data you get it in the "Final Variance Parameters"-tab of the results worksheet. Run the example data-set "Data22.PWO"; you should get:
Dependent Units Parameter Estimate If you have a higher-order design (e.g., two tests and one reference) you have to calculate it manually from the residual variance. I had some discussions with Pharsight last May; maybe it will be included in the next release of Phoenix (6.2, expected end of March).*) CVintra=sqrt(exp(Var(Residual))-1) If you have a replicate design (at least the reference administered twice) in the first window of the BE wizard select 'Type of Bioeqivalence' [•] Population/Individual (not Average!). In the result worksheet (example data-set "Seq2Per4.pwo") you should get the within-subject sigma as: SigmaWR 0.3566 Calculate CVWR=sqrt(exp(SigmaWR2)-1)=0.36825 Don't know how to calculate CVWT; consider asking at Pharsight's Extranet. *) Still not available in v6.2... — Dif-tor heh smusma 🖖🏼 Довге життя Україна! ![]() Helmut Schütz ![]() The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes |
ElMag ☆ 2011-02-24 12:16 (5171 d 19:34 ago) @ Helmut Posting: # 6667 Views: 4,334 |
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Thank you so much Helmut ! You helped me very much with your guidance! |