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Registersample size in bioequivalence studies [Power / Sample Size]
Hi daryazyatina,
For some reason, I can't see the image with the formula that you put on the first post.
Within subject standard deviation and within subject CV are different parameters. Nevertheless, I think that this is not the only reason for such a big difference.
There is a sentence in one of the articles that is quoted on SampleNTOST formula that may clarify this issue:
"This formula is less conservative than Formula (5), but it may result in a lower actual power than the required. For example, when α = 0.05, σ = 0.3, Δ = 0.2, θ = 0.01 and a required power = 0.80, the sample size from Formula (6) [Formula from Chow] is 17 per sequence, but the actual power obtained by this sample size is only 0.69."
So by reading this, I am not sure if Chow formula might be appropriate to calculate sample size for BABE trials. I have just quickly read the article, so I may not be doing a proper analysis. Perhaps dlabes might clarify this, since he is the master that we all should thank for the amazing PowerTOST package
For some reason, I can't see the image with the formula that you put on the first post.
❝ For comparison, I use all the standard properties. Design 2x2, confidence intervals 0.8 - 1.25, power 0.8, alpha 0.05.
❝ The only thing about what I'm not sure is CV. Because in formula that I used this is intra-subject variability, but in PowerTOST() this is coefficient of variation as ratio. In calculations in both cases I used СV - 0.3.
Within subject standard deviation and within subject CV are different parameters. Nevertheless, I think that this is not the only reason for such a big difference.
There is a sentence in one of the articles that is quoted on SampleNTOST formula that may clarify this issue:
"This formula is less conservative than Formula (5), but it may result in a lower actual power than the required. For example, when α = 0.05, σ = 0.3, Δ = 0.2, θ = 0.01 and a required power = 0.80, the sample size from Formula (6) [Formula from Chow] is 17 per sequence, but the actual power obtained by this sample size is only 0.69."
So by reading this, I am not sure if Chow formula might be appropriate to calculate sample size for BABE trials. I have just quickly read the article, so I may not be doing a proper analysis. Perhaps dlabes might clarify this, since he is the master that we all should thank for the amazing PowerTOST package
Complete thread:
- sample size in bioequivalence studies daryazyatina 2017-08-03 09:34 [Power / Sample Size]
![[Mix]](https://static.bebac.at/img/mix.png "open in Mix view")
- sample size in bioequivalence studies BE-proff 2017-08-03 09:55
- sample size in bioequivalence studies daryazyatina 2017-08-03 10:08
- sample size in bioequivalence studies ElMaestro 2017-08-03 10:17
- sample size in bioequivalence studies daryazyatina 2017-08-03 10:58
- sample size in bioequivalence studiesDavidManteigas 2017-08-03 12:40
- sample size in bioequivalence studies daryazyatina 2017-08-03 13:46
- Don’t use the formula by Chow, Shao, Wang! Helmut 2017-08-03 15:37
- Don’t use the formula by Chow, Shao, Wang! daryazyatina 2017-08-03 15:52
- Don’t use the formula by Chow, Shao, Wang! DavidManteigas 2017-08-03 16:12
- Don’t use the formula by Chow, Shao, Wang! Helmut 2017-08-03 16:33
- Don’t use the Book by Chow, Shao, Wang! d_labes 2017-08-16 16:01
- compromised power Helmut 2017-08-03 16:04
- compromised power daryazyatina 2017-08-04 08:15
- terminology Helmut 2017-08-04 12:41
- terminology daryazyatina 2017-08-16 10:12
- terminology Helmut 2017-08-16 18:54
- terminology daryazyatina 2017-08-16 10:12
- terminology Helmut 2017-08-04 12:41
- compromised power daryazyatina 2017-08-04 08:15
- sample size in bioequivalence studiesDavidManteigas 2017-08-03 12:40
- sample size in bioequivalence studies daryazyatina 2017-08-03 10:58
- sample size in bioequivalence studies balinskyi 2018-06-03 12:58
- sample size in bioequivalence studies BE-proff 2017-08-03 09:55
Ing. Helmut Schütz