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Re: [NMusers] ETAs & SIGMA in external validation

From: Leonid Gibiansky <>
Date: Fri, 6 Apr 2018 13:51:55 -0400

It would be better to use


(at least if the original model was fit with INTERACTION option and
residual error model is not additive).

One option is to use Para = THETA * EXP(ETA)
You would be changing the model, but the model is not too good any way
if you need to restrict Para > 0 artificially.

SIGMA should be taken from the model.


On 4/6/2018 12:32 PM, Tingjie Guo wrote:
> Dear NMusers,
> I have two questions regarding the statistical model when performing
> external validation. I have a dataset and would like to validate a
> published model with POSTHOC method i.e. $EST METHOD=0 POSTHOC MAXEVAL=0.
> 1. The model added etas in proportional way, i.e. Para = THETA * (1+ETA)
> and this made the posthoc estimation fail due to the negative individual
> parameter estimate in some subjects. I constrained it to be positive by
> adding ABS function i.e. Para = THETA * ABS(1+ETA), and the estimation
> can be successfully running. I was wondering if there is better workaround?
> 2. OMEGA value influences individual ETAs in POSTHOC estimation. Should
> we assign $SIGMA with model value or lab (where external data was
> determined) assay error value? If we use model value, it's
> understandable that $SIGMA contains unexplained variability and thus it
> is a part of the model. However, I may also understand it as that model
> value contains the unexplained variability for original data (in which
> the model was created) but not for external data. I'm a little confused
> about it. Can someone help me out?
> I would appreciate any response! Many thanks in advance!
> Your sincerely,
> Tingjie Guo

Received on Fri Apr 06 2018 - 13:51:55 EDT

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