Log in
RegisterInteresting! [General Statistics]
Hi ElMaestro,
What I've said is that the p-value for formulation as nothing to do with the statistical conclusion of bioequivalence. For the statistical evaluation of "difference in means", to be compared with the same statistical conclusion of "difference in means" with the 90% confidence interval, the p value must be assessed against the 10% significance level. So, if your 90% Confidence Interval does not contain 1, then the p-value for formulation is also significant at the 10% significance level and may or not be also significant at the 5% significance level.
The model is build the same way whether you are assessing difference in means or bioequivalence. The hypothesis are, however, different. For the hypothesis of "bioequivalence" the alpha level is 5%, and for the hypothesis of "difference in means" the alpha level is 10%. And the p-value only assess the hypothesis of difference in means. I'm sorry if I'm not explaining myself right, I'll let someone smarter try to do a better job
What I've said is that the p-value for formulation as nothing to do with the statistical conclusion of bioequivalence. For the statistical evaluation of "difference in means", to be compared with the same statistical conclusion of "difference in means" with the 90% confidence interval, the p value must be assessed against the 10% significance level. So, if your 90% Confidence Interval does not contain 1, then the p-value for formulation is also significant at the 10% significance level and may or not be also significant at the 5% significance level.
The model is build the same way whether you are assessing difference in means or bioequivalence. The hypothesis are, however, different. For the hypothesis of "bioequivalence" the alpha level is 5%, and for the hypothesis of "difference in means" the alpha level is 10%. And the p-value only assess the hypothesis of difference in means. I'm sorry if I'm not explaining myself right, I'll let someone smarter try to do a better job
Complete thread:
- Relationship between calculated 90% CI and sign. treatment effect in BE GM 2017-03-27 19:40
![[Mix]](https://static.bebac.at/img/mix.png "open in Mix view")
- 1–2α CI and TOST at α 0.05 Helmut 2017-03-27 23:47
- 1–2α CI and TOST at α 0.05 GM 2017-03-28 06:50
- 1–2α CI and TOST at α 0.05 DavidManteigas 2017-03-28 11:48
- 1–2α CI and TOST at α 0.05 ElMaestro 2017-03-28 13:12
- alpha TOST is not alpha 2-sided d_labes 2017-03-28 15:12
- Interesting! ElMaestro 2017-03-28 21:10
- Google has the answer d_labes 2017-03-29 08:20
- Interesting! DavidManteigas 2017-03-29 11:16
- Interesting! ElMaestro 2017-03-29 11:20
- Interesting!DavidManteigas 2017-03-29 12:28
- 95% CI for a test on difference d_labes 2017-03-29 14:24
- Interesting! GM 2017-03-29 20:06
- Interesting! nobody 2017-03-30 08:24
- Interesting!DavidManteigas 2017-03-29 12:28
- Interesting! ElMaestro 2017-03-29 11:20
- Interesting! ElMaestro 2017-03-28 21:10
- alpha TOST is not alpha 2-sided d_labes 2017-03-28 15:12
- Relationship between calculated 90% CI and sign. treatment effect in BE GM 2017-03-29 12:11
- Relationship between calculated 90% CI and sign. treatment effect in BE DavidManteigas 2017-03-29 12:30
- 1–2α CI and TOST at α 0.05 ElMaestro 2017-03-28 13:12
- 1–2α CI and TOST at α 0.05 DavidManteigas 2017-03-28 11:48
- 1–2α CI and TOST at α 0.05 GM 2017-03-28 06:50
- 1–2α CI and TOST at α 0.05 Helmut 2017-03-27 23:47
Ing. Helmut Schütz