From: Jun Shen <*jun.shen.ut*>

Date: Thu, 16 Oct 2008 15:17:08 -0500

Dear Elodie/Steve/Nick,

Thank you for your replies. So we can either simulate or bootstrap to

perform a visual predictive check. I just downloaded a WFN package

(developed by Nick) which is very convenient. By doing $Sim and $Est we can

get simulated data. Now I just wonder since we also get estimated parameters

(THETA, ETA, SIGMA) from simulation or bootstrap, has anyone ever used these

parameters? I mean in addition to comparing the percentiles of the DV can we

extract any useful information by looking at those parameters? Something

like, if the estimated parameters from real dataset fall within the 95%

intervals of simulated or bootstraped data? Does such comparison make any

sense?

A following question is how we export those parameters to a table. I know I

bring up old stuff. Alison and other people have posted codes. But these

codes do not seem to work for me. I wonder if anyone has successfully used

these codes.

Attached codes I found in previous discussions.

SUBROUTINE INFN (ICALL,THETA,DATREC,INDXS,NEWIND)

DIMENSION THETA(*),DATREC(*),INDXS(*)

DOUBLE PRECISION THETA

IF (ICALL.EQ.3) THEN

DO WHILE(DATA)

IF (NEWIND.LE.1) WRITE (50,*) ETA

ENDDO

WRITE (51,*) OBJECT

WRITE (52,*) THETA

WRITE (53,*) SETHET

WRITE (54,*) OMEGA(BLOCK)

WRITE (55,*) SEOMEG(BLOCK)

WRITE (56,*) SIGMA(BLOCK)

WRITE (57,*) SESIGM(BLOCK)

WRITE (58,*) IERE,IERC

ENDIF

On Tue, Oct 14, 2008 at 8:26 PM, Nick Holford <n.holford

*> Jun,
*

*>
*

*> In addition to Elodie's clear explanation of the basic process of using
*

*> $SIM and $EST in the same control stream you may wish to know that you don't
*

*> have to use the same parameters for simulation as those used for estimation.
*

*> The ICALL variable has a value of 4 when NONMEM is simulating so you can do
*

*> this:
*

*>
*

*> $THETA
*

*> 1 FIX ; sim_CL
*

*> 10 ; est_CL
*

*>
*

*> $PK
*

*>
*

*> IF (ICALL.EQ.4) THEN ; for simulation
*

*> CL=THETA(1)
*

*> ELSE ; for estimation
*

*> CL=THETA(2)
*

*> ENDIF
*

*>
*

*> Nick
*

*>
*

*>
*

*> Elodie Plan wrote:
*

*>
*

*>>
*

*>> Dear Jun,
*

*>>
*

*>> When $SIM and $EST on the same model file, the simulation will be run
*

*>> first, based on initial values, and then, afterwards, the estimation of the
*

*>> simulated data will be done, that's it, no further re-simulation based on
*

*>> the estimated parameters will follow.
*

*>>
*

*>> So what you should do is first to analyze your observed data in an
*

*>> estimation model file, and then report your estimated parameters as initial
*

*>> values to run your simulation-estimation study; this allows you to compare
*

*>> estimates of real data to estimates of simulated data, so to check
*

*>> simulation properties of your model.
*

*>>
*

*>> I hope this helps,
*

*>>
*

*>> Elodie
*

*>>
*

*>> / Elodie Plan, PharmD, MSc, ///
*

*>>
*

*>> / PhDstudent// ///
*

*>>
*

*>> /*****************************************///
*

*>>
*

*>> /Div. of Pharmacokinetics and Drug Therapy,
*

*>> Department of Pharmaceutical Biosciences,
*

*>> Faculty of Pharmacy, //Uppsala University/
*

*>>
*

*>> / PO - Box 591 - 751 24 //Uppsala - SWEDEN/
*

*>>
*

*>> /Office +46 18 4714385 - Fax +46 18 4714003
*

*>> ------------------------------------------------------------///
*

*>>
*

*>> *From:* owner-nmusers *

*>> *On Behalf Of *Jun Shen
*

*>> *Sent:* Wednesday, October 15, 2008 1:01 AM
*

*>> *To:* nmusers *

*>> *Subject:* [NMusers] How $simulation work with $estimation
*

*>>
*

*>> Dear NMusers,
*

*>>
*

*>> I wonder how does $Simulation work with $Estimation in NONMEM exactly?
*

*>> The manual says, NONMEM will simulate DVs and replace the original DVs
*

*>> based on the parameter initial values. But the initial values are not
*

*>> final
*

*>> estimates. Does the simulation based on initial values make sense? Do
*

*>> $Estimation and $Simulation run alternatively? The $Simulation generates a
*

*>> set of data based on which the parameters are estimated? And then the
*

*>> predictions are made on the estimated parameters? A little confused.
*

*>>
*

*>> Appreciate any comment.
*

*>>
*

*>> Jun
*

*>>
*

*>>
*

*> --
*

*> Nick Holford, Dept Pharmacology & Clinical Pharmacology
*

*> University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
*

*> Zealand
*

*> n.holford *

*> http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
*

*>
*

*>
*

Received on Thu Oct 16 2008 - 16:17:08 EDT

Date: Thu, 16 Oct 2008 15:17:08 -0500

Dear Elodie/Steve/Nick,

Thank you for your replies. So we can either simulate or bootstrap to

perform a visual predictive check. I just downloaded a WFN package

(developed by Nick) which is very convenient. By doing $Sim and $Est we can

get simulated data. Now I just wonder since we also get estimated parameters

(THETA, ETA, SIGMA) from simulation or bootstrap, has anyone ever used these

parameters? I mean in addition to comparing the percentiles of the DV can we

extract any useful information by looking at those parameters? Something

like, if the estimated parameters from real dataset fall within the 95%

intervals of simulated or bootstraped data? Does such comparison make any

sense?

A following question is how we export those parameters to a table. I know I

bring up old stuff. Alison and other people have posted codes. But these

codes do not seem to work for me. I wonder if anyone has successfully used

these codes.

Attached codes I found in previous discussions.

SUBROUTINE INFN (ICALL,THETA,DATREC,INDXS,NEWIND)

DIMENSION THETA(*),DATREC(*),INDXS(*)

DOUBLE PRECISION THETA

IF (ICALL.EQ.3) THEN

DO WHILE(DATA)

IF (NEWIND.LE.1) WRITE (50,*) ETA

ENDDO

WRITE (51,*) OBJECT

WRITE (52,*) THETA

WRITE (53,*) SETHET

WRITE (54,*) OMEGA(BLOCK)

WRITE (55,*) SEOMEG(BLOCK)

WRITE (56,*) SIGMA(BLOCK)

WRITE (57,*) SESIGM(BLOCK)

WRITE (58,*) IERE,IERC

ENDIF

On Tue, Oct 14, 2008 at 8:26 PM, Nick Holford <n.holford

Received on Thu Oct 16 2008 - 16:17:08 EDT