Re: Strange PRED prediction in SAEM with M3 BQL handling
Dear Andrew, Cornelis,
To add to Cornelis’s answer, likelihood function is not pdf and the integral is
not necessarily equal to 1, so I think it should not be judged by checking how
close it is to 1.
Warm regards,
Tingjie Guo
Quoted reply history
From: <[email protected]> on behalf of "Smit, Cornelis (Klinische
Farmacie)" <[email protected]>
Date: Friday, 22 February 2017 at 11:22
To: "[email protected]" <[email protected]>
Subject: RE: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Hi Andrew,
When your observation is <BLQ, M3 gives you a likelihood of this value being <
BLQ in the PRED column. So this value will be close to 1 when the model is
fairly sure that the concentration should be BLQ. This might explain why the
PREDs might be relatively high in your diagnostics here. I usually exlude the
<BLQ values in my GOF diagnostics, and check for model misspecification with a
VPC showing BLQ data (as described in
www.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2691472%2F&data=02%7C01%7C%7Cb08e3cd2c19e4b6e8a3608d698afb449%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C636864277737648346&sdata=UNUEYX%2FUiotcqhT423WbAQ1gxg%2FM6aVf%2FbcBd9bF0r8%3D&reserved=0">https://nam03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC2691472%2F&data=02%7C01%7C%7Cb08e3cd2c19e4b6e8a3608d698afb449%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C636864277737648346&sdata=UNUEYX%2FUiotcqhT423WbAQ1gxg%2FM6aVf%2FbcBd9bF0r8%3D&reserved=0
). You can do this with the old xpose package. I don’t think there is any way
to visualize the BLQ prediction in the ‘usual’ GOF but I’m very curious if
someone else has some ideas regarding this.
Kind regards,
Cornelis Smit
Hospital Pharmacist / PhD candidate
Dept. of Clinical Pharmacy
St. Antonius Hospital
Dept. of Pharmacology,
Leiden Academic Centre for Drug Research,
Leiden University, Leiden, The Netherlands
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Van: [email protected] [mailto:[email protected]] Namens
Andrew Tse
Verzonden: vrijdag 22 februari 2019 10:23
Aan: [email protected]
Onderwerp: [NMusers] Strange PRED prediction in SAEM with M3 BQL handling
Dear all,
I am running SAEM with M3 BQL handling method via PsN but having some strange
PRED values in mytab table if someone can shed some light:
I have tried using FOCE (excluding BQL data) & SAEM (excluding BQL data) both
have normal looking fitting with data in individual plots.
Once I have coded SAEM with M3 codes and include BQL data it showed very
strange PRED vs time plots (eg. 100 times over prediction at BQL time point).
IPRED had normal results.
Here are the control stream that I have used:
$PK
TVCL=THETA(1)
MU_1=LOG(TVCL)
CL=EXP(MU_1+ETA(1))
TVV2=THETA(2)
MU_2=LOG(TVV2)
V2=EXP(MU_2+ETA(2))
TVQ=THETA(3)
MU_3=LOG(TVQ)
Q=EXP(MU_3+ETA(3))
TVV3=THETA(4)
MU_4=LOG(TVV3)
V3=EXP(MU_4+ETA(4))
K23=Q/V2 ;Distribution rate constant
K32=Q/V3 ;Distribution rate constant
KA=0
A_0(1)=0
A_0(2)=0
A_0(3)=0
$DES
DADT(1)= -KA*A(1)
DADT(2)= -CL*A(2)/V2-K23*A(2)+K32*A(3)
DADT(3)= K23*A(2)-K32*A(3)
$ERROR
IPRED=A(2)/V2
W=SQRT(THETA(5)**2+((THETA(6)*IPRED)**2))
IF (LIMI.EQ.1) LIM= 0.05 ;BATCH 1
IF (LIMI.EQ.2) LIM= 0.01 ;BATCH 2
IF (LIMI.EQ.3) LIM= 0.025 ;BATCH 3
IF(BQL.EQ.0) THEN
F_FLAG=0
Y=IPRED+W*ERR(1)
ELSE
F_FLAG=1 ;BQL so Y is likelihood
Y=PHI((LIM-IPRED)/W)
ENDIF
IWRES=(DV-IPRED)/W
IRES=DV-IPRED
My question is that whether there is error in my M3 $ERROR model? or whether
PRED values for BQL means something else other than prediction for BQL data?
Thanks a lot.
Kind regards,
Andrew Tse
Research Pharmacist