Helmut Hero Vienna, Austria, 20120104 15:46 Posting: # 7863 Views: 4,951 

Dear all, a nice one: László Endrényi, László Tóthfalusi — Regards, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
earlybird Junior 20120110 14:11 @ Helmut Posting: # 7893 Views: 4,036 

Dear Helmut, thanks for this nice paper. Does this mean we can use this paper for sample size calculation (simulations?) and put FARTSSIE in the garbage? I have done a sample size estimation with FARTSSIE for example FDA, partial replicate, 80% power, ratio 90%, CV = 35% this result in N= 48. Whereas when I look in Table A3 I got N=37. Substantial less subjects! Somehow strange for me, as I would guess the more constraints the higher the sample size. Best regards, earlybird 
Ben Regular 20120112 19:22 @ earlybird Posting: # 7918 Views: 4,040 

Dear all, I also have some questions on this paper because I'm not that familiar with these procedures yet (sorry...). First they describe the method of EMA and state that this is "still Average Bioequivalence but with Expanding Limits" (and thus "the TOST procedure of Schuirmann can be directly applied"). Later they say that FDA uses scaled average BE instead, but for me equation [5] does not really differ from [3] and therefore (at this point) I don't understand why SABE is different from ABEL. (And hence I don't understand why the TOST procedure cannot be applied). Since the equation was equivalently restated from [3] to [5] this makes the impression – at least for me – that we have two different words (namely ABEL and SABE) for the same procedure. But I guess it's not supposed to be like this?! (BTW: the lower bound of equation [5] should be k and not k, shouldn't it? 'cause otherwise (m_Tm_R)/s_w equals k). So where is the substantial difference here (apart of course from the additional conditions required by EMA or FDA and the different choice of k or sigma_0)? Thank you, Ben 
Helmut Hero Vienna, Austria, 20120125 13:26 @ Ben Posting: # 8000 Views: 3,896 

Dear Ben! » […] this makes the impression – at least for me – that we have two different words (namely ABEL and SABE) for the same procedure. But I guess it's not supposed to be like this?! For an indepth review see the paper mentioned in this post; especially Section 4.4.2. » […] the lower bound of equation [5] should be k and not k, shouldn't it? Yes. This typo was probably carried over from Eq.7 of the paper mentioned above. P.S.: You have . — Regards, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
Ben Regular 20120125 17:51 @ Helmut Posting: # 8002 Views: 3,858 

» For an indepth review see the paper mentioned in this post; especially Section 4.4.2. » » […] the lower bound of equation [5] should be k and not k, shouldn't it? » Yes. This typo was probably carried over from Eq.7 of the paper mentioned above. » P.S.: You have . Thank you very much! 
d_labes Hero Berlin, Germany, 20120125 11:12 @ earlybird Posting: # 7998 Views: 4,004 

Dear earlybird! » I have done a sample size estimation with FARTSSIE for example FDA, partial replicate, 80% power, ratio 90%, CV = 35% this result in N= 48. Whereas when I look in Table A3 I got N=37. Substantial less subjects! Cave! FARTSSIE contains sW0=0.294 as regulatory constant. But Haidar et.al had proposed sW0=0.25, switching to scaled ABE also at CV=30% (corresponds to sWR=0.294). sW0=0.294 corresponds to k=0.76..., the EMA regulatory setting. You can see this if you choose consecutive the FDA approach and the EMA approach from the dropdown box. Both methods give the same sample size. With sW0=0.25 you will get N=29 from FARTSSIE with your settings. Comparison to the simulated results is difficult because FARTSSSIE obviously calculates the sample size the usual way but with widened acceptance ranges (ABEL with FDA regulatory constant), whereas the simulations had used the scaled ABE criterion directly (upper 95% CI of the linearised criterion <0). Moreover FARTSSIE uses the formulas for a balanced classical 2x2 crossover (!) correcting the obtained sample size to 0.75*n(2x2) for a 3period replicate design with 2 sequences (not partial replicate) and the approximation of the power via noncentral tdistribution. Approximate approximations . PowerTOST comes out with:require(PowerTOST) » Somehow strange for me, as I would guess the more constraints the higher the sample size. Right guess if you look at the corrected result . — Regards, Detlew 
earlybird Junior 20120126 10:44 @ d_labes Posting: # 8006 Views: 3,856 

Dear d_labes, » With sW0=0.25 you will get N=29 from FARTSSIE with your settings. OK you are right! Or as Lothar Mathäus would said: "Again what learned". » Right guess if you look at the corrected result . Well its not bad to have a good statistician on board Regards, earlybird 
d_labes Hero Berlin, Germany, 20120125 15:29 (edited by d_labes on 20120125 15:52) @ Helmut Posting: # 8001 Views: 3,969 

Dear Helmut, dear all, Here the results of sample size estimation using PowerTOST with expanded acceptance limits according to the EMA guidance for the 3period partial replicate design (example call CV < 0.35 ) compared to the ones based on simulation:power=80% Considering that:
— Regards, Detlew 