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balakotu ★ India, 2012-04-02 17:06 (5182 d 15:41 ago) Posting: # 8365 Views: 5,908 |
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Dear All, How to calculate Power in Partial/fully replicate study design based on FDA's Progesterone guidance SAS Program. Whether power is required are not in replicate study designs. Regards Kotu. |
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Helmut ★★★ ![]() Vienna, Austria, 2012-04-02 18:19 (5182 d 14:28 ago) @ balakotu Posting: # 8367 Views: 5,209 |
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Dear Kotu! ❝ How to calculate Power in Partial/fully replicate study design based on FDA's Progesterone guidance SAS Program. Whether power is required are not in replicate study designs. Power is not mentioned anywhere in the code with good reasons. Retrospective (aka a posteriori, post-hoc) power calculations are futile in bioequivalence studies (of any design). Either the study passed or not. — 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 |
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balakotu ★ India, 2012-04-17 08:11 (5168 d 00:35 ago) @ Helmut Posting: # 8424 Views: 4,938 |
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Dear Vienna, you said ❝ power calculations are futile in bioequivalence studies (of any design). Either the study passed or not. some time based on less power we are conduction two stage appraoch. but you said power calculations are futile why? Regards Kotu. |
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Helmut ★★★ ![]() Vienna, Austria, 2012-04-25 18:32 (5159 d 14:14 ago) @ balakotu Posting: # 8462 Views: 4,974 |
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Dear Mumbai! ![]() ❝ Dear Vienna,
❝ some time based on less power we are conduction two stage appraoch. but you said power calculations are futile why? Two Stage studies can help in dealing with uncertain CVs – e.g., if you have only data from literature, old studies, or small pilot studies. The power calculation in the interim analysis is part of the decision tree; no post-hoc power calculation should be performed. What I said about conventional BE studies is applicable here as well: Either the study passed or not. See also Potvin et al. (2008), Example 2, Method B: […] we obtain a two-sided CI for the ratio (T/R) of geometric means of 88.45—116.38%, which meets the 80—125% acceptance criterion. We stop here and conclude BE, irrespective of the fact that we have not yet achieved the desired power of 80% (power = 66.3%). (my emphasis)— 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 |
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lindseyk ● 2012-04-27 18:25 (5157 d 14:21 ago) @ Helmut Posting: # 8468 Views: 4,803 |
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Hello, Could post-hoc power analyses help in a pilot study with two test formulations compared to 1 reference in deciding which formulation to go forward with in a pivotal study? Edit: Full quote removed. Please delete anything from the text of the original poster which is not necessary in understanding your answer; see also this post! [Ohlbe] |
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Helmut ★★★ ![]() Vienna, Austria, 2012-04-28 05:12 (5157 d 03:34 ago) @ lindseyk Posting: # 8469 Views: 4,831 |
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Hi Lindsay! ❝ Could post-hoc power analyses help in a pilot study with two test formulations compared to 1 reference in deciding which formulation to go forward with in a pivotal study? No – what would you expect to gain? In any higher-order Xover (e.g., 3×3 Latin Squares, 6×3 Williams’ design) you get only a common estimate of the intra-subject variance. So it boils down to assessing the point estimates T1/R and T2/R. Select the one closer to 100%. Theoretically [sic] you could run a replicate design to assess the intra-subject variances of formulations as well. If the test/reference ratios are similar (or one is the reciprocal of the other) you could select the one with lower variability. But with two tests you will end up with a f**ing complicated replicate design with many periods, even if you a apply a modified Balaam’s design. Haven’t seen any such a study in 30+ years… ![]() — 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 |

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