Re: [NMusers] Incorporating standard deviation (SD) on fitted mean values

From: Paul Matthias Diderichsen <pmdiderichsen_at_wequantify.com>
Date: Tue, 17 Nov 2015 08:43:18 +0100

Hi Ahmad,
In your aggregate data, ETA describes between-study variability while
EPS describes the between-subject variability. As such, EPS is not
"unexplained" (as in RUV) but rather "explained" in the data.

You can interpret the residual error in NONMEM as a weight of your data.
If you have small sample size or large BSV for a given outcome, then you
should not put as much weight on that data point = larger variance.

Precision is a different beast altogether: this relates to the standard
error of your estimates (= variance-covariance matrix), and depends
(everything else being equal) on how much data you have.

(I'm looping this back into NMUsers; maybe somebody else has comments)

On 11/17/2015 0:34, Abu Helwa, Ahmad Yousef Mohammad - abuay010 wrote:
> Hi Paul,
>
> Thank you for your input on this. However, in the case you presented, the SD in the error model will then informs about the precision rather than between subject variability? In my case, the parameter I am modelling (gastric pH) is measured in X number of subjects and the mean and SD are reported. So, the SD is not the precision of the measurement within a subjects (the measurement in each subject was performed one time), rather, it is between subjects. The large SDs for some of the reported means is due to the fact that BSV in gastric pH is high.
>
> Ahmad.
>
> -----Original Message-----
> From: Paul Matthias Diderichsen [mailto:pmdiderichsen_at_wequantify.com]
> Sent: Monday, 16 November 2015 6:16 PM
> To: Abu Helwa, Ahmad Yousef Mohammad - abuay010 <ahmad.abuhelwa_at_mymail.unisa.edu.au>
> Subject: Re: [NMusers] Incorporating standard deviation (SD) on fitted mean values
>
> Hi Ahmad,
>
> On 11/15/2015 23:46, Abu Helwa, Ahmad Yousef Mohammad - abuay010 wrote:
>> Y = IPRED *(1+EPS(1)/SQRT(NSUB))
>> 5) Is there any way where I can incorporate the SDs that I have to
>> inform about the between SUBJECT variability in the model fitting?
>
> Include the reported SD (REPSD) in your residual error variance and fix
> the sigma to 1 (the variance is defined in your data). I would probably
> describe the mean as a normal distributed variable, so:
>
> Y = IPRED + EPS(1)*REPSD/SQRT(NSUB)
> $SIGMA
> 1 FIX
>
>
>
> Kind regards,
>


--
Paul Matthias Diderichsen, PhD
Quantitative Solutions, a Certara company
+31 624 330 706
Received on Tue Nov 17 2015 - 02:43:18 EST

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