Re: Incorporating standard deviation (SD) on fitted mean values
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)
Quoted reply history
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:[email protected]]
> Sent: Monday, 16 November 2015 6:16 PM
> To: Abu Helwa, Ahmad Yousef Mohammad - abuay010
> <[email protected]>
> 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