Re: [NMusers] Simulations with/without residual error

2009-07-08 Thread Nick Holford 

Andreas,

My suggestion:

If you want to compare your simulations with actual observations then 
you should include residual error in the simulation. The observations 
will include noise as well as the 'true' value so in order to compare 
observations with simulated observations you need the residual error.


If you want to use the simulation to describe the 'true' value then dont 
include the residual error. Residual error is assumed to have a mean of 
zero around the 'true' value so there is no point in adding this kind of 
noise if you are trying to predict the 'true' value.


Your examples suggest to me that you are trying to predict the 'true' 
value -- not trying to match simulations directly with measured values. 
If my guess is correct then you dont need to include residual error.


However, if you are using simulations for some kind of predictive check 
(visual, numerical, statistical) that will be compared to distribution 
statistics of the observations then you should include residual error.


Nick

andreas lindauer wrote:


Dear NMUSERS,

 

The recent discussion about simulation with a nonparametric method 
brought a general question concerning monte-carlo simulations into my 
mind. When should simulations be performed with residual error and 
when not. I am especially interested in comments regarding the 
following scenarios when the result of the simulation should be 
reported as mean or median and 90% prediction interval:


1. Simulated response at a particular time point (eg. Trough values)

2. Simulated response at a particular time point (x) relative to 
baseline response (IPRED(t=x)/IPRED(t=0) vs. DV(t=x)/DV(t=0) )


3. Simulated time of maximal response (eg. Tmax)

 

 


Thanks and best regards, Andreas.

 

 




 


Andreas Lindauer

 


Department of Clinical Pharmacy

Institute of Pharmacy

University of Bonn

An der Immenburg 4

D-53121 Bonn

 


phone: + 49 228 73 5781

fax:  + 49 228 73 9757

 



--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holf...@auckland.ac.nz tel:+64(9)923-6730 fax:+64(9)373-7090
mobile: +33 64 271-6369 (Apr 6-Jul 20 2009)
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

RE: [NMusers] Simulations with/without residual error

2009-07-07 Thread Grevel, Joachim 
Dear NMUsers,
 
I cannot see a reason to leave out the residual error. We all know how error 
shifts around between IIV, IOV, and residual error. A large residual error is 
indeed troublesome even when all other model parameters would indicate a good 
fit with small shrinkage. You only recognize the trouble when you start 
simulating the kind of responses listed by Andreas. You may have to conclude in 
the end that your model is not very predictive because of large residual error 
(=large, still unexplained variability).
 
Joachim Grevel 
 
AstraZeneca R&D Charnwood 
Clin. Pharmacology and DMPK 
Bakewell Road 
Loughborough, LE11 5RH 
Tel: +44 1509 64 5177 
joachim.gre...@astrazeneca.com 


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-Original Message-
From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com]on 
Behalf Of andreas lindauer
Sent: 07 July 2009 10:34
To: nmusers@globomaxnm.com
Subject: [NMusers] Simulations with/without residual error



Dear NMUSERS,

 

The recent discussion about simulation with a nonparametric method brought a 
general question concerning monte-carlo simulations into my mind. When should 
simulations be performed with residual error and when not. I am especially 
interested in comments regarding the following scenarios when the result of the 
simulation should be reported as mean or median and 90% prediction interval: 

1. Simulated response at a particular time point (eg. Trough values)

2. Simulated response at a particular time point (x) relative to baseline 
response (IPRED(t=x)/IPRED(t=0) vs. DV(t=x)/DV(t=0) )

3. Simulated time of maximal response (eg. Tmax)

 

 

Thanks and best regards, Andreas.

 

 



 

Andreas Lindauer

 

Department of Clinical Pharmacy

Institute of Pharmacy

University of Bonn

An der Immenburg 4

D-53121 Bonn

 

phone: + 49 228 73 5781

fax:  + 49 228 73 9757