NONMEM Users Network Archive

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RE: Simulation with uncertainty

From: Anne-Gaelle Dosne <annegaelle.dosne>
Date: Mon, 5 Aug 2013 09:37:34 +0200

Dear Dinko,

 

As Jakob already mentioned, the assumptions we are making when =
simulating
with parameter uncertainty using the variance-covariance matrix or the
bootstrap are the same as when we use these techniques to get confidence
intervals around model parameters. For the covariance matrix, we assume =
the
parameter vectors arise from a multivariate normal distribution given by =
the
asymptotic covariance matrix. For the bootstrap, parameter vectors arise
from each bootstrapped dataset, so there is no assumption about a global
parameter distribution.

 

Both of these methods can have drawbacks, in particular when one is far =
from
asymptotic conditions (problematic for covariance matrices) or when =
datasets
have few individuals, many stratas, or when the bootstrap is not =
problematic
(see Niebecker et al. PAGE 2013). Another alternative to simulate with
parameter uncertainty is to use Sampling Importance Resampling, which I
presented at PAGE this year. The principle is to simulate parameter =
vectors
from the covariance matrix, but add a step where they are evaluated on =
the
original data. Weights are then assigned to each parameter vector
representing how likely they are given the data at hand, and based on =
these
weights you can sample parameter vectors to use for simulation with
uncertainty.

 

Best regards,

 

Anne-GaŽlle

 

-------------------------------------------------------

Anne-GaŽlle Dosne, PharmD, PhD student

Pharmacometrics Research Group,

Department of Pharmaceutical Biosciences,

Uppsala University

PO Box 591 - 751 24 Uppsala - Sweden

 

Mobile: +46 725 859 870

Email: annegaelle.dosne

--------------------------------------------------------

 

 

From: owner-nmusers
On
Behalf Of Dinko Rekic
Sent: 01 August 2013 18:55
To: nmusers
Subject: [NMusers] Simulation with uncertainty

 

Dear NMusers,

I would like to get your thoughts on some common used techniques for
simulation with uncertainty. If one is interested in simulating the =
expected
mean response, there are two methods that are can be employed:

(1) Use the variance-covariance matrix
(2) Use of bootstrap results.

What assumptions are we making when using each of the methods? What are =
the
respective prose and cons? Do you have any preference in terms of when =
to
use method 1 over 2 or vice versa?

Thanks and kind regards
//Dinko


Received on Mon Aug 05 2013 - 03:37:34 EDT

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