fyy897854960 Junior China, 20181101 09:28 (edited by mittyri on 20181101 11:53) Posting: # 19512 Views: 373 

Dear All, I have some questions about the Partial SS in Bioequivalence results in WinNonlin. Firstly, why the Partial SS results just provided under default model(2x2x2 design) in WinNonlin 8.1? It just provides the Partial test worksheet in other models. What are the differences and relationship between the Partial test results and Partial SS results? Secondly, what are the Numer_DF and Denom_DF? What is the calculation method for these DF since it could be decimals in Degrees of freedom sometimes. Just like the following results: Dependent Units Hypothesis Numer_DF Denom_DF F_stat P_value Ln(AUClast) int 1 17.863275 2.012866 0.17318289 Ln(AUClast) Sequence 1 17.876226 9.2107972 0.007163829 Ln(AUClast) Formulation 1 17.189233 0.19446307 0.66472393 Ln(AUClast) Period 1 17.202333 0.67862197 0.42133666 Could you kindky help me with these questions? Thank you very much, Fu Yangyang Edit: Category changed; see also this post #1. [Mittyri] 
mittyri Senior Russia, 20181101 11:50 @ fyy897854960 Posting: # 19513 Views: 325 

Dear Fu Yangyang, » Firstly, why the Partial SS results just provided under default model(2x2x2 design) in WinNonlin 8.1? Note that General Linear Model is applicable for a model without additional variance structures (PURE ANOVA). Partial SS is very similar to SS type III table provided by SAS (GLM procedure) » It just provides the Partial test worksheet in other models. What are the differences and relationship between the Partial test results and Partial SS results? RTFM (WNL User's guide)! Partial Tests worksheet » Secondly, what are the Numer_DF and Denom_DF? What is the calculation method for these DF since it could be decimals in Degrees of freedom sometimes. Same source: The default calculation method of the degrees of freedom is controlled on the General Options tab and is initially set to Satterthwaite. With that method of DF approximation float DFs are likely, especially in case of some inbalance. PS: Aren't you satisfied with Certara Support Forum? — Kind regards, Mittyri 
fyy897854960 Junior China, 20181101 14:16 (edited by mittyri on 20181101 16:26) @ mittyri Posting: # 19517 Views: 316 

» PS: Aren't you satisfied with Certara Support Forum? Sometimes I can not get timely reply. So I post my question here. Anyway, thanks again. Fu Edit: Full quote removed. Please delete everything from the text of the original poster which is not necessary in understanding your answer; see also this post #5! [Mittyri] 
ElMaestro Hero Denmark, 20181101 22:49 @ fyy897854960 Posting: # 19518 Views: 289 

Hi Fyy et al., I am not a SAS user or a WNL user, but I think the basis for this question may be a little wrong? In a 222BE trial the result is generally produced with a linear model, not a mixed model, regardless of authority. In that situation the whole concept of denominator df's if irrelevant. The residual df's will be an integer. So, I am guessing you fit your model with subject as random, and hence it becomes a mixed model. If I recall correctly WNL happily fits subject as random by default so one may need to actively tell the beast that everything including subject is fixed. Then the analysis becomes compliant with guidelines and expectation, and there will be no denominator df's to confuse you. — if (3) 4 Best regards, ElMaestro "(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures." New York Times (ed.), June 9, 2018. 
Helmut Hero Vienna, Austria, 20181101 23:12 @ ElMaestro Posting: # 19519 Views: 283 

Hi ElMaestro et al., » In a 222BE trial the result is generally produced with a linear model, not a mixed model, regardless of authority. […]» » If I recall correctly WNL happily fits subject as random by default so one may need to actively tell the beast that everything including subject is fixed. Yep. It is possible to set that in the preferences of Phoenix for a good while (too lazy to search since when). Then any study will be evaluated with fixed effects only. @Fu Yangyang: RTFM. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
mittyri Senior Russia, 20181102 11:19 @ ElMaestro Posting: # 19524 Views: 255 

Hi ElMaestro et al., » In a 222BE trial the result is generally produced with a linear model, not a mixed model, regardless of authority. In that situation the whole concept of denominator df's if irrelevant. The residual df's will be an integer. Yes, that's correct. I think the second topicstarter's question is related to replicate designs. » So, I am guessing you fit your model with subject as random, and hence it becomes a mixed model. In SAS (and R) the user is free to to use different approaches with different procedures (i.e. PROC GLM, PROC MIXED ...). In WNL you have only one module which is MIXED by default. But what about RANDOM statements inside PROC GLM (remember the usual FDA SAS code for sinple 2X2 crossover)? See the guide: Fixed effects model: Sequence + Formulation + Period But is it MIXED or GLM+RANDOM? Later: Since there is no repeated specification, the default error model ε ~ N(0, σ^{2} I) is used. This is equivalent to the classical analysis method, but using maximum likelihood instead of method of moments to estimate intersubject variance. Using Subject as a random effect this way, the correct standard errors will be computed for sequence means and tests of sequence effects. Here ya go! This is GLM with RANDOM! That's important hidden feature:  the design (replicate/nonreplicate) is caught on the fly,  for 2X2 bioequivalence fixed(Sequence + Formulation + Period), Subject as Random mean GLM+RANDOM,  for replicated designs the default model is the model proposed by FDA (also EMA Method C): Fixed effects model: Sequence + Formulation + Period And you need to manually change the model to use EMA ABEL (Method A or B)  for replicated designs fixed(Sequence + Formulation + Period) and Subject as Random mean MIXED model (and you don't get SS, DFs could be floats). This is EMA Method B.  To switch to ANOVA with replicated designs you need to manually move subject to fixed terms tab and remove everything from Random Tab. PS: all these things Simon and other trainers are explaining during training sessions — Kind regards, Mittyri 