Statistical power of covariate inclusion in popPK models
Hi,
Thank you all for your answers. I have two follow-up questions:
1. Is it mandatory to use the matrix R as a variance co-variance matrix
to obtain the FIM? In case we have already used other type of variance
co-variance matrix, should we rerun the model with matrix R setting?
2. How critical is the estimation method for the computed SE? In other
words, is it relevant to compare two powers computed based on two standard
errors givens by different estimation algorithms?
For example, if we used FOCE-INTER to minimize our model, could we compare the
power (based on the Wald test) to results given by PFIM which is based on FO ?
Just for a little bit of background to clarify why we are interested in the
Wald test.
We are working on the comparison of different methods to compute the
statistical power of covariate inclusion in popPK models (SSE (gold standard),
MCMP, PPE , and Wald test). We have also included the Wald test in our
comparison because it is the fastest method and mostly because it used by
optimal designs software. Therefore, the evaluation of the accuracy of the
power derived by this method could facilitate the bridging step between model
validation and the design of upcoming clinical trials using optimal design
software.
Thank you in advance.
Cordially.
Ibtihel HAMMAMI.