RE: IIV on res error
Hi Yuma,
IIV on residual error is effectively compound symmetry. What it is saying is
that "some subjects are more variable than others" without suggesting a reason
why. Your model below incorporates additive error, and you don't have IIV on
F1, so in your case, this ETA on EPS could be one of:
* Masking proportional error on PK
* Masking dose-related variability in PK if subjects received different
doses
* Masking IIV on F1
* True compound symmetry where some subjects are more variable than
others
There are probably other options, but I would check some of those to see if
they can improve your model before using ETA on EPS.
Thanks,
Bill
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Y.A. Bijleveld
Sent: Friday, January 16, 2015 9:09 AM
To: [email protected]
Subject: [NMusers] IIV on res error
Dear all,
I am modeling multi-center log-transformed neonatal data and have constructed a
2-compartment model with ETA's on Cl, V1 and V2. However, when introducing
interindividual variability on the residual error the MOFV drops >150 points,
while previously significant relationships between clearance and covariates
disappear. I find it strange that the introduction of the IIV has such an
impact and don't fully understand. I have already checked the data for
(extreme) outliers.
Can anyone shed some light?
Thank you so much.
Yuma Bijleveld.
$PK
F1=(BIO1**FDS12) * (BIO2**FDS34)
TVV1=THETA(1)*(WT/70000)
V1=TVV1*EXP(ETA(1))
TVCL=THETA(2)*(WT/70000)**0.75*(GA/281)**THETA(6)
CL=TVCL*EXP(ETA(2))
TVQ=THETA(4)*(WT/70000)**0.75
Q=TVQ
TVV2=THETA(5)*(WT/70000)
V2=TVV2*EXP(ETA(3))
S1=V1
$ERROR
IPRED=LOG(0.0001)
IF(F.GT.0)IPRED=LOG(F)
IRES = DV-IPRED
W=1
IF(F.GT.0)W = SQRT(THETA(3)**2)
IWRES = IRES/W
Y = IPRED+W*EPS(1)*EXP(ETA(4))
$THETA
(0, 75.7) ;1 V1
(0, 2.09) ;2 CL
(0, 0.376) ;3 add
(0, 3) ;4 Q
(0, 31.8) ;5 V2
(0, 3.3) ;6 GA
$OMEGA BLOCK(2)
0.167 ;1 V1
0.0824 0.12 ;2 Cl
$OMEGA
0.1 ;3 V2
$OMEGA
0.1 ;4 RES
$SIGMA
1 FIX
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