Variance independent from mean [General Statistics]
Hi Zan,
If you talk about the intra-subject CV of treatments, yes.
Correct. In the 2×2 the ISCV is actually derived from a common variance of the treatment ones. If treatment variances are substantially different (e.g., high for a ‘bad’ reference and low for a ‘good’ test), the residual error – and therefore the CI – will be inflated. That’s why we need high sample sizes for 2×2 Xovers of HVDPs – the test will be punished for the reference’s CV. In (fully) replicated design together with RSABE in this case you will get a reward in terms of sample size. But that’s somehow OT.
I don’t think so. Imagine the distribution (normal or lognormal, doesn’t matter). It is defined by two parameters, the mean and the variance. These two are independent.
![[image]](img/uploaded/image249.png)
![[image]](img/uploaded/image250.png)
❝ My knowledge to obtain an accurate intrasubject CV% is to conduct a replicated crossover design dosing same formulation twice.
If you talk about the intra-subject CV of treatments, yes.
❝ From a 2x2 crossover study where signiciant treatment effects exist, eg. a significant food-effect study, we are still able to obtain the intrasub CV% from the output.
Correct. In the 2×2 the ISCV is actually derived from a common variance of the treatment ones. If treatment variances are substantially different (e.g., high for a ‘bad’ reference and low for a ‘good’ test), the residual error – and therefore the CI – will be inflated. That’s why we need high sample sizes for 2×2 Xovers of HVDPs – the test will be punished for the reference’s CV. In (fully) replicated design together with RSABE in this case you will get a reward in terms of sample size. But that’s somehow OT.
❝ As I was going to use these intrasub CV% to help biostats to est sample size for a BE study, someone challenged that these number are not real and are likely inflated due to the signficant treatment effect. Is it true?
I don’t think so. Imagine the distribution (normal or lognormal, doesn’t matter). It is defined by two parameters, the mean and the variance. These two are independent.
![[image]](img/uploaded/image249.png)
![[image]](img/uploaded/image250.png)
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Complete thread:
- Estimate of Intrasubject CV from a study with TX effect zan 2014-01-30 00:08
- Variance independent from meanHelmut 2014-01-30 02:12
- Variance independent from mean zan 2014-01-30 18:26
- Estimate of Intrasubject CV from a study with TX effect ElMaestro 2014-01-30 08:38
- Variance independent from meanHelmut 2014-01-30 02:12