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Re: COND LAPLACE LIKELIHOOD

From: Leonid Gibiansky <LGibiansky>
Date: Tue, 04 Aug 2009 16:33:49 -0400

something is incorrect here, either model or comments:
   P0 = C0/(1+C0) ; Probability of Score=>0
   P1 = C1/(1+C1) ; Probability of Score=>1
   P2 = C2/(1+C2) ; Probability of Score=>2

Probability of Score=>0 is always 1 (because score is 0 or positive
number as I can see).

My guess is that the model is incorrect, it should be (assuming that the
drug increases probability of higher scores while natural state favors
score 0)

> A1 = B1 + DRUG
> A2 = B1 - B2 + DRUG
> A3 = B1 - B2 - B3 + DRUG

> C1 = EXP(A1)
> C2 = EXP(A2)
> C3 = EXP(A3)
> P1 = C1/(1+C1) ; Probability of Score=>1
> P2 = C2/(1+C2) ; Probability of Score=>2
> P3 = C3/(1+C3) ; Probability of Score=>3
>
> PR0 = 1-P1 ; Probability of Score=0
> PR1 = P1-P2 ; Probability of Score=1
> PR2 = P2-P3 ; Probability of Score=2
> PR3 = P3 ; 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

  B2 and B3 should be positive

--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566




wangx826
> 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 - 16:33:49 EDT

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