yicaoting Regular NanKing, China, 20170822 18:01 Posting: # 17736 Views: 1,478 

Dear Helmut, Hope you are well. I am trying to manually calculate the upper 90% CL of sWT/sWR in US FDA's RSABE for NTIDs(Draft Guidance on Warfarin). I use BEBAC's sample data (page 14 of the PPT from this site) to validate/verify my calculation steps. Data set link http://bebac.at/downloads/NTID.xls It will be greatly appreciated if you can help me on the following questions: 1. I manually calculate the sWR and sWT in Excel sheet, they are 0.124392769, 0.055720909, respectively. Are my results EXACTELY right? 2. In your slides, you have present the upper 95% CL of sWT/sWR 0.68427 ≤2.5. I have calculated lower 95% CL of sWT/sWR = 0.293238292 upper 95% CL of sWT/sWR = 0.684266753 (this is nearly the same as your result) As US FDA's Guidance on Warfarin required, the upper 90% CI should be used, I also calculate the following: lower 90% CL of sWT/sWR = 0.322597242 upper 90% CL of sWT/sWR = 0.621992961 Are the above results right? I use the function Finv(0.1,16,16) and Finv(0.9,16,16) for the calculation of 90% CL of sWT/sWR, and Finv(0.05,16,16) and Finv(0.95,16,16) for the calculation of 95% CL of sWT/sWR. Do I use the right function? 2. Would you please guide (step by step) me how to calculate CVwr CVwt? As shown in your slides, they are CVWR 12.49%, CVWT 5.58%. Although these two values are not used in calculation of "upper 90% CL of sWT/sWR". Thank you for your great sample dataset which provides us a valuable bridge for us to learn and discuss this sparely used procedure. 
Helmut Hero Vienna, Austria, 20170822 20:25 @ yicaoting Posting: # 17739 Views: 1,278 

Hi Zhang Yong, » Hope you are well. THX! Below my results obtained in Phoenix WinNonlin 7.0 in full precision. » I manually calculate the sWR and sWT in Excel sheet, they are 0.124392769, 0.055720909, respectively. Are my results EXACTELY right? s_{wR} 0.124392768691665, s_{wT} 0.0557209092013223 » In your slides, you have present the upper 95% CL of sWT/sWR 0.68427 ≤2.5. » I have calculated » lower 95% CL of sWT/sWR = 0.293238292 » upper 95% CL of sWT/sWR = 0.684266753 (this is nearly the same as your result) lower CL 0.293238291752988, upper CL 0.684266752752176 » As US FDA's Guidance on Warfarin required, the upper 90% CI should be used, I also calculate the following: » lower 90% CL of sWT/sWR = 0.322597242 » upper 90% CL of sWT/sWR = 0.621992961 » Are the above results right? The guidance might be confusing. See the last bullet point below the formula
» I use the function Finv(0.1,16,16) and Finv(0.9,16,16) for the calculation of 90% CL of sWT/sWR, » and Finv(0.05,16,16) and Finv(0.95,16,16) for the calculation of 95% CL of sWT/sWR. Do I use the right function? I have only Excel 2000. Up to v2003 the inverse distributions were wrong. Maybe you have to use F.inv(alpha,df1,df1) or the old workaround Finv(2*alpha,df1,df1) . Duno. The correct Fvalues (ν_{1}=ν_{2}=16) are:F_{α∕2,ν1,ν2} 2.33348362746764, F_{1−α∕2,ν1,ν2} 0.428543825304327 » Would you please guide (step by step) me how to calculate CVwr CVwt? As shown in your slides, they are CVWR 12.49%, CVWT 5.58%. Although these two values are not used in calculation of "upper 90% CL of sWT/sWR". According to the guidance s_{WR} and s_{wT} are estimated from complete data only (not an issue with this data set) ignoring its structure (solely 'sequence' in the linear model). Your values are correct. Hence, as usual CV_{w} = 100√ℯ^{s²w}  1. Therefore, we get CV_{wR} 12.49% and CV_{wT} 5.58%. Personally I would prefer to run a mixed effects model with restricted maximum likelihood which takes the entire information into account (i.e., the FDA’s code of the 2001 guidance and also in the ABEpart of the progesterone guidance). In this model you could have incomplete data and the variances of R and T are simultaneously estimated. I guess that’s impossible in Excel (as it is in R)… I got: CV_{wR} 15.86% and CV_{wT} 5.73%. Interesting. Hope that helps. — Regards, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
yicaoting Regular NanKing, China, 20170823 05:30 @ Helmut Posting: # 17742 Views: 1,240 

Hi, Helmut. Thank you for your quick response. » THX! Below my results obtained in Phoenix WinNonlin 7.0 in full precision. » s_{wR} 0.124392768691665, s_{wT} 0.0557209092013223 Yes, sWR and sWT can be calculate manually. So my results are indentical to yours. » lower CL 0.293238291752988, upper CL 0.684266752752176 Thay are identical to mine. » The guidance might be confusing. See the last bullet point below the formula
I am not sure the guidance is correct or not. But from the formula in the guidance (page 4, line 5) with Alpha=0.1, I guess the guidance is right, it calulates 90% CI of Swt/Swr, but not 95% CI. Need your clarification? or FDA is wrong? » I have only Excel 2000. Up to v2003 the inverse distributions were wrong. Maybe you have to use F.inv(alpha,df1,df1) or the old workaround Finv(2*alpha,df1,df1) . Duno. The correct Fvalues (ν_{1}=ν_{2}=16) are:» F_{α∕2,ν1,ν2} 2.33348362746764, F_{1−α∕2,ν1,ν2} 0.428543825304327 In Excel 2003, Finv(0.05,16,16) = 2.33348362835 Finv(0.95,16,16) = 0.428543825142279 In Excel 2013 Finv(0.05,16,16) = 2.33348362746764 Finv(0.95,16,16) = 0.428543825304327 F.inv(0.05,16,16) = 0.428543825304327 F.inv(0.95,16,16) = 2.33348362746764 » According to the guidance s_{WR} and s_{wT} are estimated from complete data only (not an issue with this data set) ignoring its structure (solely 'sequence' in the linear model). Your values are correct. Hence, as usual CV_{w} = 100√ℯ^{s²w}  1. Therefore, we get CV_{wR} 12.49% and CV_{wT} 5.58%. Thanks. » Personally I would prefer to run a mixed effects model with restricted maximum likelihood which takes the entire information into account (i.e., the FDA’s code of the 2001 guidance and also in the ABEpart of the progesterone guidance). In this model you could have incomplete data and the variances of R and T are simultaneously estimated. I guess that’s impossible in Excel (as it is in R)… » I got: CV_{wR} 15.86% and CV_{wT} 5.73%. Interesting. I guess your result of 15.86% and 5.73% are obtain from the sheet of "Final Variance Parameters" from ABE results using PHX WNL. let a = Var(Period*Formulation*Subject)_21 (the value is 0.024828963992548 from PHX WNL) b = Var(Period*Formulation*Subject)_22 (the value is 0.003281299568883 from PHX WNL) CVwr = 100 * SQRT(EXP(a)1) CVwt = 100 * SQRT(EXP(b)1) I got the same results sa you. Here the CVwr and CVwt are different from those calculated from Swr and Swt. I prefer the result calculated from Swr and Swt. What's your opinion? 
Helmut Hero Vienna, Austria, 20170823 15:00 @ yicaoting Posting: # 17744 Views: 1,204 

Hi Zhang Yong, » But from the formula in the guidance (page 4, line 5) with Alpha=0.1, I guess the guidance is right, it calulates 90% CI of Swt/Swr, but not 95% CI. » Need your clarification? or FDA is wrong? The FDA is never wrong. But so am I. The guidance asks to calculate an confidence interval but only the upper confidence limit is assessed. Simply: The 90% CI has an upper and lower 95% CL. » » Personally I would prefer […] to run a mixed effects model with restricted maximum likelihood… » » I got: CV_{wR} 15.86% and CV_{wT} 5.73%. Interesting. » » I guess your result of 15.86% and 5.73% are obtain from the sheet of "Final Variance Parameters" from ABE results using PHX WNL. Correct. » Here the CVwr and CVwt are different from those calculated from Swr and Swt. » I prefer the result calculated from Swr and Swt. » What's your opinion? For my preferences see above. If you have to follow the guidance that’s not an option. BTW, if you have Phoenix WinNonlin why bother fiddling around in Excel? I have some doubts whether an agency will accept that. At least the EMA wouldn’t. Quoting the Q&A document: 3.3. Alternative computer programs — Regards, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
yicaoting Regular NanKing, China, 20170830 14:33 @ Helmut Posting: # 17756 Views: 1,044 

Hi Helmut For validation of statistical procedure or software in analysis of BE data of NTID. I am eagerly hope you publish such reference datasets, like those two papers published in AAPS J in 2015 for two way crossover and parallel design. If you wish, please tell me If i can provide any help. I now use WNL PHX and SAS and/or Excel to analysis NTID. Excel is used just for SigmaWR and SigmaWR/SigmaWT and it's upper llevel of %CI, not for ABE or RSABE in such case. BTW, I have developed a program in VBA in Excel for BE analysis, it has passed all 2*2*2 and 2‖2 reference datasets you provided. This program is not intended for commercialization, but will be published for free use in future. Like PKSolver and DDSolver which have been published. 
Helmut Hero Vienna, Austria, 20170830 15:04 @ yicaoting Posting: # 17757 Views: 1,029 

Hi Yong, » I am eagerly hope you publish such reference datasets, like those two papers published in AAPS J in 2015 for two way crossover and parallel design. We are working on a paper for the EMA’s ABEL. We will also provide an Rpackage. It is still a work in progress. Its current state on GitHub. In the inst/extdata folder our reference data sets. NTIDs are DS02.csv (TRRRTRRRT), DS05.csv (TRRTRTTR), and DS10.csv (TRRRTT). Sorry, none with TRTRRTRT…» I now use WNL PHX and SAS and/or Excel to analysis NTID. Excel is used just for SigmaWR and SigmaWR/SigmaWT and it's upper llevel of %CI, not for ABE or RSABE in such case. Our results with replicateBE and the latest template for PHX/WNL:DS05.csv: s_{wT}∕s_{wR} 1.0184, upper CL of σ_{wT}∕σ_{wR} 1.4344. DS10.csv: s_{wT}∕s_{wR} 1.2566, upper CL of σ_{wT}∕σ_{wR} 2.3300. » BTW, I have developed a program in VBA in Excel for BE analysis, it has passed all 2*2*2 and 2‖2 reference datasets you provided. This program is not intended for commercialization, but will be published for free use in future. Like PKSolver and DDSolver which have been published. Great! — Regards, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 