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RE: [EXTERNAL] RE: Statistical power computation based on the wald test

From: Bauer, Robert <Robert.Bauer>
Date: Wed, 24 Mar 2021 18:18:06 +0000

Hello all:
I would just like to add some information to help the discussion along.

In addition to the variance-covariance matrix that is outputted in the .cov=
 file that Ken mentioned, the Fisher information matrix itself (inverse of =
variance-covariance) is also outputted in the .coi file. Additional files=
, such as .rmt (R matrix), and .smt (S matrix) are also outputted upon user=
 request ($COV PRINT=RS, for example)

A test related to Wald and log-likelihood ratio tests is the Lagrange Multi=
plier test. For this purpose, NONMEM outputs the following in the .ext fil=
Iteration -1000000008 lists the partial derivative of the log likelihood (-=
1/2 OFV) with respect to each estimated parameter.

PFIM, POPED, and NONMEM's $DESIGN calculate the expected FIM with respect t=
o the data, and the expected value R matrix is equivalent to the expected v=
alue of the S matrix. That is, Ey(R)= Ey(S).

Several companion/interface software to NONMEM have additional model evalua=
tion facilities, such as stepwise covariate model (scm) building in Perl Sp=
eaks NONMEM, and Wald test in PDxPop.

Robert J. Bauer, Ph.D.
Senior Director
Pharmacometrics R&D
ICON Early Phase
820 W. Diamond Avenue
Suite 100
Gaithersburg, MD 20878
Office: (215) 616-6428
Mobile: (925) 286-0769
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Received on Wed Mar 24 2021 - 14:18:06 EDT

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