Why do we need pooled CV? [Power / Sample Size]
Hi BE_Proff,
Yah it is tricky. You need a CV guess to plan a sample size in yur next trial. You may not know anything in advance, so best you can do (?) may be to look up CV's in the literature.
Using the highest CV as you say is conservative, not necessarily a bad idea, and will work in your favour in terms of power.
For once I actually disagree with Helmut. At least, I think I do if I got his post right.
To me pooled CV is not always an obvious answer. It is one proposal, but I do not know if it is any better than other proposals.
Pooled variances work through sample sizes - somehow pooled CV's weight the different trials according to sample sizes and then work out an overall estimate from them.
I think this approach "academizes" (is that even a word?) the issue. While the calculation looks fancy with greek sigmas and all, I think it is every bit as useful -if not considerably more useful, even- to read info about the various trials you have access to and ask yourself which one or which ones you think are most solid scientifically. It could be based on CRO reputation, assay technique, bioanalytical A+P details, year, equipment, LLOQ, whatever you have access to. Add to that something which is so extremely important in BE but which by definition cannot be defined scientifically: Gut feeling. Never forget gut feeling. It is what makes you stand out positively from the crowd.
❝ As my statistics background is rather poor (shame on me) I can't understand purpose of pooled CV in BE-studies.
Yah it is tricky. You need a CV guess to plan a sample size in yur next trial. You may not know anything in advance, so best you can do (?) may be to look up CV's in the literature.
❝ But what prevents us from using the highest CV for sample size calculation?
Using the highest CV as you say is conservative, not necessarily a bad idea, and will work in your favour in terms of power.
For once I actually disagree with Helmut. At least, I think I do if I got his post right.
To me pooled CV is not always an obvious answer. It is one proposal, but I do not know if it is any better than other proposals.
Pooled variances work through sample sizes - somehow pooled CV's weight the different trials according to sample sizes and then work out an overall estimate from them.
I think this approach "academizes" (is that even a word?) the issue. While the calculation looks fancy with greek sigmas and all, I think it is every bit as useful -if not considerably more useful, even- to read info about the various trials you have access to and ask yourself which one or which ones you think are most solid scientifically. It could be based on CRO reputation, assay technique, bioanalytical A+P details, year, equipment, LLOQ, whatever you have access to. Add to that something which is so extremely important in BE but which by definition cannot be defined scientifically: Gut feeling. Never forget gut feeling. It is what makes you stand out positively from the crowd.
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Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
Complete thread:
- Why do we need pooled CV? BE-proff 2016-08-24 08:48 [Power / Sample Size]
- Maximum CV might be misleading Helmut 2016-08-24 12:07
- Maximum CV might be misleading BE-proff 2016-08-26 10:41
- Pooling – example Helmut 2016-08-26 11:34
- Pooling – example BE-proff 2016-12-28 14:37
- in my protocols… Helmut 2016-12-29 12:27
- Pooling – example BE-proff 2016-12-28 14:37
- Pooling – example Helmut 2016-08-26 11:34
- Maximum CV might be misleading BE-proff 2016-08-26 10:41
- Why do we need pooled CV?ElMaestro 2016-08-24 13:03
- Yessir! Common sense! Helmut 2016-08-24 13:53
- Common sense weighting before pooling mittyri 2016-08-24 15:13
- Gut feeling is the answer! DavidManteigas 2016-08-25 11:09
- The reasons not to pool Astea 2016-08-26 20:40
- The reasons not to pool mittyri 2016-08-28 22:05
- Know your drug/formulation! Helmut 2016-08-29 11:56
- The reasons not to pool Astea 2016-08-26 20:40
- Yessir! Common sense! Helmut 2016-08-24 13:53
- Maximum CV might be misleading Helmut 2016-08-24 12:07