Re: Strange PRED prediction in SAEM with M3 BQL handling
One can get PRED at BQLs using COMACT option, see manual:
"COMACT=1 is a pass with final thetas and zero-valued etas".
Things computed at this stage are based on THETAS with zero ETAs and thus provide PRED values. E.g.,
IPRED = ...
IF(COMACT==1) PRED1=IPRED
creates the PRED1 variable that is a population prediction even at BQL records.
Have not tried it but it looks like it can be used to create population predictions of other derived variables as well (like AUC, half-life, etc.) that need to be computed based on THETAs (with ETAs equal to zero).
Leonid
Quoted reply history
On 2/22/2019 5:11 AM, Smit, Cornelis (Klinische Farmacie) wrote:
> 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 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2691472/ ). 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