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:[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
