From: kyunseop.bae

Date: Tue, 24 Feb 2009 12:07:30 -0800

Hi, Ethan,

I think your question can be reduced whether pseudo-inverse matrix can be

used instead of inverse matrix.

I do not know quite different cases, but I suppose it can be used.

To be more adequate answer in your context,

MATRIX=R option could be more appropriate,

if you use VAR-COV matrix output for simulation under normal distribution

assumtion,

If your data supports normal distribution assumption, MATRIX=R option will

not give much difference in SEs.

Default VAR-COV output in NONMEM is a kind of sandwich estimate, which is

thought to be more robust (a little larger) than inverse Fisher's

information matrix (given MATRIX=R option).

Some caution is necessary to simulate omega matrix that is alwasy positive

definite.

This may help you.

Thanks,

Kyun Seop Bae MD PhD

Email: kyunseop.bae

________________________________

From: owner-nmusers

Behalf Of Ethan Wu

Sent: Tuesday, February 24, 2009 11:09 AM

To: justin.wilkins

Cc: nmusers

Subject: Re: [NMusers] var-cov matrix issue?

Hi Justin, only ETA was estimated with high SE

but, again, I guess it came back to the question: how trustful it is if such

error message appears

________________________________

From: justin.wilkins

To: ethan.wu75

Sent: Tuesday, February 24, 2009 1:19:17 PM

Subject: Fw: [NMusers] var-cov matrix issue?

Dear Ethan,

Algorithmically singular matrices are often a sign that that your model is

ill-conditioned in some way; I would be careful in how I used the

variance-covariance matrix in this scenario, and especially for simulation.

Are there any parameters that are being estimated with particularly high

standard errors? This might suggest overparamaterization.

Not sure how helpful this is!

Best

Justin

Justin Wilkins

Senior Modeler

Modeling & Simulation (Pharmacology)

CHBS, WSJ-027.6.076

Novartis Pharma AG

Lichtstrasse 35

CH-4056 Basel

Switzerland

Phone: +41 61 324 6549

Fax: +41 61 324 3039

Cell: +41 76 561 0949

Email : justin.wilkins

----- Forwarded by Justin Wilkins/PH/Novartis on 2009/02/24 07:15 PM -----

Ethan Wu <ethan.wu75

Sent by: owner-nmusers

2009/02/24 07:12 PM

To

nmusers

cc

Subject

[NMusers] var-cov matrix issue?

Dear all,

I recently encounter this error message (below). My objective was to use

nonmem var-cov output for approximation of distribution of parameters for

performing a simulation.

if such error message occur, is the var-cov matrix still OK to use?

-- I know that better way to figure out distribution of parameters is to do

bootstrap, but given limited time I have.....

thanks

"0MINIMIZATION SUCCESSFUL

NO. OF FUNCTION EVALUATIONS USED: 331

NO. OF SIG. DIGITS IN FINAL EST.: 3.3

ETABAR IS THE ARITHMETIC MEAN OF THE ETA-ESTIMATES,

AND THE P-VALUE IS GIVEN FOR THE NULL HYPOTHESIS THAT THE TRUE MEAN IS 0.

ETABAR: 0.11E-02

SE: 0.23E-01

P VAL.: 0.96E+00

0S MATRIX ALGORITHMICALLY SINGULAR

0S MATRIX IS OUTPUT

0INVERSE COVARIANCE MATRIX SET TO RS*R, WHERE S* IS A PSEUDO INVERSE OF S

1

"

Received on Tue Feb 24 2009 - 15:07:30 EST

Date: Tue, 24 Feb 2009 12:07:30 -0800

Hi, Ethan,

I think your question can be reduced whether pseudo-inverse matrix can be

used instead of inverse matrix.

I do not know quite different cases, but I suppose it can be used.

To be more adequate answer in your context,

MATRIX=R option could be more appropriate,

if you use VAR-COV matrix output for simulation under normal distribution

assumtion,

If your data supports normal distribution assumption, MATRIX=R option will

not give much difference in SEs.

Default VAR-COV output in NONMEM is a kind of sandwich estimate, which is

thought to be more robust (a little larger) than inverse Fisher's

information matrix (given MATRIX=R option).

Some caution is necessary to simulate omega matrix that is alwasy positive

definite.

This may help you.

Thanks,

Kyun Seop Bae MD PhD

Email: kyunseop.bae

________________________________

From: owner-nmusers

Behalf Of Ethan Wu

Sent: Tuesday, February 24, 2009 11:09 AM

To: justin.wilkins

Cc: nmusers

Subject: Re: [NMusers] var-cov matrix issue?

Hi Justin, only ETA was estimated with high SE

but, again, I guess it came back to the question: how trustful it is if such

error message appears

________________________________

From: justin.wilkins

To: ethan.wu75

Sent: Tuesday, February 24, 2009 1:19:17 PM

Subject: Fw: [NMusers] var-cov matrix issue?

Dear Ethan,

Algorithmically singular matrices are often a sign that that your model is

ill-conditioned in some way; I would be careful in how I used the

variance-covariance matrix in this scenario, and especially for simulation.

Are there any parameters that are being estimated with particularly high

standard errors? This might suggest overparamaterization.

Not sure how helpful this is!

Best

Justin

Justin Wilkins

Senior Modeler

Modeling & Simulation (Pharmacology)

CHBS, WSJ-027.6.076

Novartis Pharma AG

Lichtstrasse 35

CH-4056 Basel

Switzerland

Phone: +41 61 324 6549

Fax: +41 61 324 3039

Cell: +41 76 561 0949

Email : justin.wilkins

----- Forwarded by Justin Wilkins/PH/Novartis on 2009/02/24 07:15 PM -----

Ethan Wu <ethan.wu75

Sent by: owner-nmusers

2009/02/24 07:12 PM

To

nmusers

cc

Subject

[NMusers] var-cov matrix issue?

Dear all,

I recently encounter this error message (below). My objective was to use

nonmem var-cov output for approximation of distribution of parameters for

performing a simulation.

if such error message occur, is the var-cov matrix still OK to use?

-- I know that better way to figure out distribution of parameters is to do

bootstrap, but given limited time I have.....

thanks

"0MINIMIZATION SUCCESSFUL

NO. OF FUNCTION EVALUATIONS USED: 331

NO. OF SIG. DIGITS IN FINAL EST.: 3.3

ETABAR IS THE ARITHMETIC MEAN OF THE ETA-ESTIMATES,

AND THE P-VALUE IS GIVEN FOR THE NULL HYPOTHESIS THAT THE TRUE MEAN IS 0.

ETABAR: 0.11E-02

SE: 0.23E-01

P VAL.: 0.96E+00

0S MATRIX ALGORITHMICALLY SINGULAR

0S MATRIX IS OUTPUT

0INVERSE COVARIANCE MATRIX SET TO RS*R, WHERE S* IS A PSEUDO INVERSE OF S

1

"

Received on Tue Feb 24 2009 - 15:07:30 EST