Re: computation of exponential error model for RUV
Dear Monia,
Yes, that is correct.
So if one were to use this parameterization for FOCE then one would effectively
get a proportional (symmetric) error distribution, exactly according to what
you suggested:
Y=F*(1+EPS(1))
For this reason, the standard approach in NONMEM (for FOCE and exponential
RUV), is to log-transform both sides, i.e.like this:
$ERROR (OBSERVATION ONLY)
DEL=0.0000001
IPRED=LOG(F+DEL)
Y=IPRED+EPS(1)
So additive on the log-transformed scale is exactly the error model you would
like to use.
Maybe that would be a solution for your comparison?
Best wishes
Jakob
Quoted reply history
> On 19 Jul 2021, at 17:34, Guidi Monia <[email protected]> wrote:
>
> Dear colleagues,
>
> We would like to compare the NONMEM predictions with those obtained by a
> Bayesian TDM software for models describing the residual unexplained
> variability with exponential errors.
>
> We need to know if NONMEM performs a first order Taylor expansion of the
> exponential error when data are fitted by the FOCE method:
> Y=F*EXP(EPS(1)) -> Y= F*(1+EPS(1)).
>
> Could someone help with this?
> Thanks in advance
> Monia
>
> Monia Guidi, PhD
>
> Pharmacometrician
> Service of Clinical Pharmacology | University Hospital and University of
> Lausanne
> Center of research and innovation in Clinical Pharmaceutical Sciences |
> University Hospital and University of Lausanne
> BU17 01/193
> CH-1011 Lausanne
> email: [email protected] <mailto:[email protected]>
> tel: +41 21 314 38 97
>
>
> CHUV
> centre hospitalier universitaire vaudois
>
> <image001.png>
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