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RE: COND LAPLACE LIKELIHOOD

From: wangx826
Date: 04 Aug 2009 14:23:12 -0500

Hi Samer,
 Thanks for your quick reply. Here is my control stream:

$SUBS ADVAN6 TOL=6
$MODEL
COMP=(ABSO)
COMP=(CENT)
COMP=(PERI)
COMP=(EFFECT)
$PK
   CL =ICL*24
   V2 = IVC
   Q=...
   K23=Q/V2
   V3=
   K32=Q/V3
   K=CL/V2
   KA=...
   KE0 = THETA(6)
   B1 = THETA(1)
   B2 = THETA(2)
   B3 = THETA(3)
   EMAX = THETA(4)
   EC50 = THETA(5)*EXP(ETA(1))

$DES
DADT(1)=-A(1)*KA
DADT(2)=A(1)*KA-A(2)*K23+A(3)*K32-A(2)*K
DADT(3)=A(2)*K23-A(3)*K32
DADT(4)=KE0*(A(2)/V2-A(4))

$ERROR
   CE=A(4)
   DRUG = EMAX*CE/(EC50+CE)
   A0 = B1 + DRUG
   A1 = B1 + B2 + DRUG
   A2 = B1 + B2 + B3 + DRUG
   C0 = EXP(A0)
   C1 = EXP(A1)
   C2 = EXP(A2)
   P0 = C0/(1+C0) ; Probability of Score=>0
   P1 = C1/(1+C1) ; Probability of Score=>1
   P2 = C2/(1+C2) ; Probability of Score=>2

   PR0 = P0 ; Probability of Score=0
   PR1 = P1-P0 ; Probability of Score=1
   PR2 = P2-P1 ; Probability of Score=2
   PR3 = 1-P2 ; Probability of Score=3
   
   IF (DV.EQ.0) Y=PR0
   IF (DV.EQ.1) Y=PR1
   IF (DV.EQ.2) Y=PR2
   IF (DV.EQ.3) Y=PR3

 $THETA (-20 -6.3) ; THETA1 B1
 $THETA (-10 -0.3) ; THETA2 B2
 $THETA (-10 2) ; THETA3 B3
 $THETA (0 5) ; THETA4 EMAX
 $THETA (0 50) ; THETA5 EC50
 $THETA (0 1) ; THETA6 KEO

 $OMEGA 2

 $ESTIMATION MAXEVAL=9999 PRINT=5 METHOD=COND LAPLACIAN LIKELIHOOD
  NOABORT MSFO=MSF1

Here I include the dataset for first two subjects. Since it is a
simultaneous PKPD link model, DV in the data set as follows is categorical=
 
PD data. The dose was given daily and DV was recorded daily as well.
#SUBJ TIME AMT EVID II ADDL PD KA CL V2 MDV
1 0 . 0 . . 0 9.96 4.12 63.57 0
1 0 1 1 1 20 . 9.96 4.12 63.57 1
1 1 . 0 . . 0 9.96 4.12 63.57 0
1 2 . 0 . . 0 9.96 4.12 63.57 0
1 3 . 0 . . 0 9.96 4.12 63.57 0
1 4 . 0 . . 0 9.96 4.12 63.57 0
1 5 . 0 . . 0 9.96 4.12 63.57 0
1 6 . 0 . . 0 9.96 4.12 63.57 0
1 7 . 0 . . 0 9.96 4.12 63.57 0
1 8 . 0 . . 0 9.96 4.12 63.57 0
1 9 . 0 . . 0 9.96 4.12 63.57 0
1 10 . 0 . . 0 9.96 4.12 63.57 0
1 11 . 0 . . 0 9.96 4.12 63.57 0
1 12 . 0 . . 0 9.96 4.12 63.57 0
1 13 . 0 . . 0 9.96 4.12 63.57 0
1 14 . 0 . . 0 9.96 4.12 63.57 0
1 15 . 0 . . 0 9.96 4.12 63.57 0
1 16 . 0 . . 0 9.96 4.12 63.57 0
1 17 . 0 . . 0 9.96 4.12 63.57 0
1 18 . 0 . . 0 9.96 4.12 63.57 0
1 19 . 0 . . 0 9.96 4.12 63.57 0
1 20 . 0 . . 0 9.96 4.12 63.57 0
1 21 . 0 . . 0 9.96 4.12 63.57 0
1 22 . 0 . . 0 9.96 4.12 63.57 0
1 23 . 0 . . 0 9.96 4.12 63.57 0
1 24 . 0 . . 0 9.96 4.12 63.57 0
1 25 . 0 . . 0 9.96 4.12 63.57 0
1 26 . 0 . . 0 9.96 4.12 63.57 0
1 27 . 0 . . 0 9.96 4.12 63.57 0
2 0 . 0 . . 0 1.52 4.68 66.91 0
2 0 2 1 1 20 . 1.52 4.68 66.91 1
2 1 . 0 . . 0 1.52 4.68 66.91 0
2 2 . 0 . . 0 1.52 4.68 66.91 0
2 3 . 0 . . 0 1.52 4.68 66.91 0
2 4 . 0 . . 0 1.52 4.68 66.91 0
2 5 . 0 . . 0 1.52 4.68 66.91 0
2 6 . 0 . . 0 1.52 4.68 66.91 0
2 7 . 0 . . 0 1.52 4.68 66.91 0
2 8 . 0 . . 0 1.52 4.68 66.91 0
2 9 . 0 . . 0 1.52 4.68 66.91 0
2 10 . 0 . . 0 1.52 4.68 66.91 0
2 11 . 0 . . 0 1.52 4.68 66.91 0
2 12 . 0 . . 1 1.52 4.68 66.91 0
2 13 . 0 . . 1 1.52 4.68 66.91 0
2 14 . 0 . . 1 1.52 4.68 66.91 0
2 15 . 0 . . 1 1.52 4.68 66.91 0
2 16 . 0 . . 1 1.52 4.68 66.91 0
2 17 . 0 . . 1 1.52 4.68 66.91 0
2 18 . 0 . . 1 1.52 4.68 66.91 0
2 19 . 0 . . 1 1.52 4.68 66.91 0
2 20 . 0 . . 1 1.52 4.68 66.91 0
2 21 . 0 . . 3 1.52 4.68 66.91 0
2 22 . 0 . . 3 1.52 4.68 66.91 0
2 23 . 0 . . 3 1.52 4.68 66.91 0
2 24 . 0 . . 3 1.52 4.68 66.91 0
2 25 . 0 . . 3 1.52 4.68 66.91 0
2 26 . 0 . . 3 1.52 4.68 66.91 0
2 27 . 0 . . 3 1.52 4.68 66.91 0
2 28 . 0 . . 2 1.52 4.68 66.91 0

Thanks,
Tianli
***************************************************************************=
***
Tianli Wang
University of Minnesota,
Department of Pharmaceutics

On Aug 4 2009, Samer Mouksassi wrote:

>Can you include your control (or at least your $EST bloc)
>And the proportional odds PD data. The likelihood may go wild if some
>categories are very rare or non esistent. You need to gard against over
>or underflow.
>
>-----Original Message-----
>From: owner-nmusers
>On Behalf Of wangx826
>Sent: 2009-08-04 13:38
>To: NMUSERS
>Subject: [NMusers] COND LAPLACE LIKELIHOOD
>
>Dear nmusers,
>
>Has anybody seen the following error message from NONMEM:
>"CONDITIONAL LIKELIHOOD SET TO NEGATIVE VALUE
> WITH INDIVIDUAL 2 (IN INDIVIDUAL RECORD ORDERING), DATA RECORD 13"?
>What does it mean?
>
>I am trying to use conditional lapalacian likelihood method to generate
>a
>proportional odds model dealing with categorical PD data. Here is a
>little
>piece of my data set:
>SUBJ TIME AMT EVID II ADDL DV CL V
>MDV
>2 0 . 0 . . 0 4.12 63
>0
>2 0 1 1 1 20 . 4.12 63
>1
>2 0.005 . 2 . . . 4.12 63
>1
>2 0.01 . 2 . . . 4.12 63
>1
>.
>.
>.
>2 12 . 0 . . 0 4.12 63
>0
>2 13 . 0 . . 1 4.12 63
>0
>.
>.
>.
>But I don't think the problem exists in the data set because I tried
>deleting the rows indicated in the error message, but the exactly same
>message still came out and NONMEM stopped running. I have no idea what's
>
>the problem for my model.
>
>Thanks in advance,
>
>Tianli
>
Received on Tue Aug 04 2009 - 15:23:12 EDT

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