Post-hoc power is useless! [Study Assessment]
Dear Detlew,
If post-hoc power is useless why power calculations are used in Potvin methods for sequential designs?
There is nothing wrong with post-hoc power calculations imo. What is wrong is the conclusions you take from it and if you look at post-hoc power alone to justify a failure. As I stated, for studies that fail to demonstrate bioequivalence a lot other methods to "dig" into the failure could be used. As El Maestro stated GMRs and CVs may be more informative alone, but in fact I believe they all provide a similar conclusion. When I look at post-hoc power, GMRs and CVs what I'm trying to check is if the problem was in the formulation or in the number of subjects included in the study.
That being said, power calculations or CVs alone are not the way I use to check data for explanation of failures. As I stated, I like to check individual ratios and to perform sensitivity analysis by removing "extreme" subjects and check how the overall conclusion is affected. Sometimes, the explanation for those failures may be in those extreme subjects and discussions with clinical operations may unleash some problems not evident from the data collected. Pooling data from several studies in the same unit is also useful to check for potential "trends" in outlying values, although I never had the opportunity to do that.
Regards,
David
If post-hoc power is useless why power calculations are used in Potvin methods for sequential designs?
There is nothing wrong with post-hoc power calculations imo. What is wrong is the conclusions you take from it and if you look at post-hoc power alone to justify a failure. As I stated, for studies that fail to demonstrate bioequivalence a lot other methods to "dig" into the failure could be used. As El Maestro stated GMRs and CVs may be more informative alone, but in fact I believe they all provide a similar conclusion. When I look at post-hoc power, GMRs and CVs what I'm trying to check is if the problem was in the formulation or in the number of subjects included in the study.
That being said, power calculations or CVs alone are not the way I use to check data for explanation of failures. As I stated, I like to check individual ratios and to perform sensitivity analysis by removing "extreme" subjects and check how the overall conclusion is affected. Sometimes, the explanation for those failures may be in those extreme subjects and discussions with clinical operations may unleash some problems not evident from the data collected. Pooling data from several studies in the same unit is also useful to check for potential "trends" in outlying values, although I never had the opportunity to do that.
Regards,
David
Complete thread:
- How to understand what is guilty? BE-proff 2016-07-30 18:21 [Study Assessment]
- How to understand what is guilty? ElMaestro 2016-07-30 23:15
- How to understand what is guilty? BE-proff 2016-08-02 17:06
- How to understand what is guilty? DavidManteigas 2016-08-08 11:18
- Post-hoc power is useless! d_labes 2016-08-09 08:31
- Post-hoc power is useless! ElMaestro 2016-08-09 13:00
- Post-hoc power is useless! d_labes 2016-08-09 14:30
- Post-hoc power is useless! ElMaestro 2016-08-09 16:17
- Post-hoc power is useless! d_labes 2016-08-09 14:30
- Post-hoc power is useless!DavidManteigas 2016-08-09 13:51
- Post-hoc power is useless! d_labes 2016-08-09 14:11
- Post-hoc power is useless! ElMaestro 2016-08-09 13:00
- Post-hoc power is useless! d_labes 2016-08-09 08:31
- How to understand what is guilty? ElMaestro 2016-07-30 23:15