how to construct confidence interval for un-transformed metric? [Power / Sample Size]
Hi lizhao,
Some example from the ordinary guidance:
![[image]](img/uploaded/image377.png)
It could be the difference or the ratio.
It is common practice to suppose normal distribution of clinical endpoints.
BTW be aware, are you sure that your clinical endpoint is distributed normally?
Exactly (+/-0.2)
Some example from the ordinary guidance:
![[image]](img/uploaded/image377.png)
❝ For clinical endpoints, I suppose the log-normal distribution doesn't hold, therefore I should use un-transformed data to construct the 90% confidence interval? Then it would be the confidence interval of mean Test/Reference ratio? Am I correct?
It could be the difference or the ratio.
It is common practice to suppose normal distribution of clinical endpoints.
BTW be aware, are you sure that your clinical endpoint is distributed normally?
❝ But then, would the acceptance limits become 80% to 120% instead?
Exactly (+/-0.2)
—
Kind regards,
Mittyri
Kind regards,
Mittyri
Complete thread:
- how to construct confidence interval for un-transformed metric? lizhao 2016-02-17 19:01 [Power / Sample Size]
- how to construct confidence interval for un-transformed metric? jag009 2016-02-17 20:43
- how to construct confidence interval for un-transformed metric?mittyri 2016-02-17 22:34
- Fieller’s confidence interval Helmut 2016-02-18 13:38
- Fieller’s confidence interval lizhao 2016-02-22 20:20
- Fieller’s confidence interval yjlee168 2016-02-23 08:23
- Rescue approaching – PowerTOST d_labes 2016-02-23 09:08
- Rescue approaching – PowerTOST Weidson 2024-11-28 23:15
- Why not base 🇷? Helmut 2024-12-03 13:39
- Rescue approaching – PowerTOST Weidson 2024-11-28 23:15
- Fieller’s confidence interval lizhao 2016-02-22 20:20
- Fieller’s confidence interval Helmut 2016-02-18 13:38