From: Ethan Wu <*ethan.wu75*>

Date: Thu, 26 Feb 2009 04:05:23 -0800 (PST)

Dear Kyun, thanks for your help. I don't know if I understand this one=

"Some caution is necessary to simulate omega matrix that is alwasy posi=

tive definite. " Could you explain a bit more? __________=

______________________ From: "kyunseop.bae

..com> To: Ethan Wu <ethan.wu75

Sent: Tuesday, February 24, 2009 3:07:30 PM Subject: RE: [NMusers] var-co=

v matrix issue? Hi, Ethan, I think your question can be reduced w=

hether 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 a=

ppropriate, if you use VAR-COV matrix output for simulation under normal =

distribution assumtion, If your data supports normal distribution as=

sumption, MATRIX=R option will not give much difference in SEs. Defau=

lt VAR-COV output in NONMEM is a kind of sandwich estimate, which is thou=

ght to be more robust (a little larger) than inverse Fisher's information=

matrix (given MATRIX=R option). Some caution is necessary to simula=

te omega matrix that is alwasy positive definite. This may help you=

.. Thanks, Kyun Seop Bae MD PhD Email: kyunseop.bae

obomaxnm.com [mailto:owner-nmusers

com Cc: nmusers

sue? 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 mes=

sage appears ________________________________ From: "justin.wi=

lkins

m Sent: Tuesday, February 24, 2009 1:19:17 PM Subject: Fw: [NMusers] va=

r-cov matrix issue? Dear Ethan, Algorithmically singular matr=

ices 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 a=

re being estimated with particularly high standard errors? This might sug=

gest overparamaterization. Not sure how helpful this is! Best =

rmacology) CHBS, WSJ-027.6.076 Novartis Pharma AG Lichtstrasse 35 C=

H-4056 Basel Switzerland Phone: +41 61 324 6549 Fax: +41 61 324 3039=

in.wilkins

vartis on 2009/02/24 07:15 PM ----- Ethan Wu <ethan.wu75

To nmusers

ject [NMusers] var-cov matrix issue? =

Dear all, I recently encounter this error messa=

ge (below). My objective was to use nonmem var-cov output for approxim=

ation of distribution of parameters for performing a simulation. if su=

ch error message occur, is the var-cov matrix still OK to use? -- I k=

now that better way to figure out distribution of parameters is to do boo=

tstrap, but given limited time I have..... thanks "0MIN=

IMIZATION SUCCESSFUL NO. OF FUNCTION EVALUATIONS USED: 331 NO. OF SI=

G. 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 TRU=

E MEAN IS 0. ETABAR: 0.11E-02 SE: 0.23E-01 P VAL.: =

0.96E+00 0S MATRIX ALGORITHMICALLY SINGULAR 0S MATRIX IS OUTPUT 0INV=

ERSE COVARIANCE MATRIX SET TO RS*R, WHERE S* IS A PSEUDO INVERSE OF S 1=

Received on Thu Feb 26 2009 - 07:05:23 EST

Date: Thu, 26 Feb 2009 04:05:23 -0800 (PST)

Dear Kyun, thanks for your help. I don't know if I understand this one=

"Some caution is necessary to simulate omega matrix that is alwasy posi=

tive definite. " Could you explain a bit more? __________=

______________________ From: "kyunseop.bae

..com> To: Ethan Wu <ethan.wu75

Sent: Tuesday, February 24, 2009 3:07:30 PM Subject: RE: [NMusers] var-co=

v matrix issue? Hi, Ethan, I think your question can be reduced w=

hether 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 a=

ppropriate, if you use VAR-COV matrix output for simulation under normal =

distribution assumtion, If your data supports normal distribution as=

sumption, MATRIX=R option will not give much difference in SEs. Defau=

lt VAR-COV output in NONMEM is a kind of sandwich estimate, which is thou=

ght to be more robust (a little larger) than inverse Fisher's information=

matrix (given MATRIX=R option). Some caution is necessary to simula=

te omega matrix that is alwasy positive definite. This may help you=

.. Thanks, Kyun Seop Bae MD PhD Email: kyunseop.bae

obomaxnm.com [mailto:owner-nmusers

com Cc: nmusers

sue? 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 mes=

sage appears ________________________________ From: "justin.wi=

lkins

m Sent: Tuesday, February 24, 2009 1:19:17 PM Subject: Fw: [NMusers] va=

r-cov matrix issue? Dear Ethan, Algorithmically singular matr=

ices 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 a=

re being estimated with particularly high standard errors? This might sug=

gest overparamaterization. Not sure how helpful this is! Best =

rmacology) CHBS, WSJ-027.6.076 Novartis Pharma AG Lichtstrasse 35 C=

H-4056 Basel Switzerland Phone: +41 61 324 6549 Fax: +41 61 324 3039=

in.wilkins

vartis on 2009/02/24 07:15 PM ----- Ethan Wu <ethan.wu75

To nmusers

ject [NMusers] var-cov matrix issue? =

Dear all, I recently encounter this error messa=

ge (below). My objective was to use nonmem var-cov output for approxim=

ation of distribution of parameters for performing a simulation. if su=

ch error message occur, is the var-cov matrix still OK to use? -- I k=

now that better way to figure out distribution of parameters is to do boo=

tstrap, but given limited time I have..... thanks "0MIN=

IMIZATION SUCCESSFUL NO. OF FUNCTION EVALUATIONS USED: 331 NO. OF SI=

G. 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 TRU=

E MEAN IS 0. ETABAR: 0.11E-02 SE: 0.23E-01 P VAL.: =

0.96E+00 0S MATRIX ALGORITHMICALLY SINGULAR 0S MATRIX IS OUTPUT 0INV=

ERSE COVARIANCE MATRIX SET TO RS*R, WHERE S* IS A PSEUDO INVERSE OF S 1=

Received on Thu Feb 26 2009 - 07:05:23 EST