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

From: Ken Kowalski <kgkowalski58>
Date: Wed, 24 Mar 2021 16:33:46 -0400

Hi Bob,

 

Just a point of clarification. If the default sandwich estimator is used t=
o estimate the covariance matrix then the .coi file outputs the inverse of =
this sandwich estimator, ie., R(S^-1)R …correct? If so, and maybe =
this is just semantics but I don’t think we would refer to R(S^-1)R=
 as the Fisher information matrix. However, both R and S can be considered=
 equivalent FIM under certain regularity conditions. Nevertheless, if one =
wanted to determine a D-optimal design I suppose maximizing the determinant=
 of R(S^-1)R could be a reasonable thing to do. Your thoughts?

 

Ken

 

Kenneth G. Kowalski

Kowalski PMetrics Consulting, LLC

Email: <mailto:kgkowalski58

Cell: 248-207-5082

 

 

 

From: owner-nmusers
 Behalf Of Bauer, Robert
Sent: Wednesday, March 24, 2021 2:18 PM
To: nmusers
Subject: RE: [EXTERNAL] RE: [NMusers] Statistical power computation based o=
n the wald test

 

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=
e:

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 r=
espect to the data, and the expected value R matrix is equivalent to the ex=
pected value 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

Robert.Bauer

www.iconplc.com <http://www.iconplc.com>

 



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Received on Wed Mar 24 2021 - 16:33:46 EDT

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