From: Ken Kowalski <*kgkowalski58*>

Date: Mon, 22 Mar 2021 10:34:35 -0400

Hi Ibtihel,

I think you are probably asking for covariance matrix of the parameter

estimates. This should automatically be outputted as the .cov file assuming

that the $COV step runs successfully. Note that since NONMEM minimizes a

function related to -2LL, the Hessian (R matrix) in NONMEM is equivalent to

Fisher's Informaton matrix. I know you can print the R matrix in the NONMEM

output and I assume this can also be outputted to a file.perhaps others

might know

I'll leave it for you to decide whether you really want to perform power

calculations say to design/justify a sample size to detect the covariate

effect using a Wald-based test as opposed to performing simulations and

relying on a likelihood ratio test.

Ken

Kenneth G. Kowalski

Kowalski PMetrics Consulting, LLC

Email: <mailto:kgkowalski58

Cell: 248-207-5082

From: owner-nmusers

Behalf Of Hammami, Ibtihel /FR

Sent: Monday, March 22, 2021 9:22 AM

To: nmusers

Subject: [NMusers] Statistical power computation based on the wald test

Hi,

We would like to compute a covariate inclusion statistical power based on

the Wald test and using SE given by the fisher information matrix.

Is there any method to implement this directly in NONMEM or is there at

least a way to output the Fisher Information matrix in NONMEM?

Thank you.

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Received on Mon Mar 22 2021 - 10:34:35 EDT

Date: Mon, 22 Mar 2021 10:34:35 -0400

Hi Ibtihel,

I think you are probably asking for covariance matrix of the parameter

estimates. This should automatically be outputted as the .cov file assuming

that the $COV step runs successfully. Note that since NONMEM minimizes a

function related to -2LL, the Hessian (R matrix) in NONMEM is equivalent to

Fisher's Informaton matrix. I know you can print the R matrix in the NONMEM

output and I assume this can also be outputted to a file.perhaps others

might know

I'll leave it for you to decide whether you really want to perform power

calculations say to design/justify a sample size to detect the covariate

effect using a Wald-based test as opposed to performing simulations and

relying on a likelihood ratio test.

Ken

Kenneth G. Kowalski

Kowalski PMetrics Consulting, LLC

Email: <mailto:kgkowalski58

Cell: 248-207-5082

From: owner-nmusers

Behalf Of Hammami, Ibtihel /FR

Sent: Monday, March 22, 2021 9:22 AM

To: nmusers

Subject: [NMusers] Statistical power computation based on the wald test

Hi,

We would like to compute a covariate inclusion statistical power based on

the Wald test and using SE given by the fisher information matrix.

Is there any method to implement this directly in NONMEM or is there at

least a way to output the Fisher Information matrix in NONMEM?

Thank you.

--

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Received on Mon Mar 22 2021 - 10:34:35 EDT