From: joannellyn.y.chiu@gsk.com Subject: [NMusers] Error when combining proportional residual error, Date: Wed, 2 Aug 2006 10:41:49 -0400 Hi, My model had 4 proportional (eps 1,3,5,7) and 4 (eps 2,4,6,8) additive residual errors. I had wanted to combine the proportional errors (eps 1,3 & eps 5,7) but wanted to leave the additive residual errors individually. when i did this, I received an error that states: 0PROGRAM TERMINATED BY OBJ ERROR IN CELS WITH INDIVIDUAL 934 ID=0.93400000E+03 WEIGHTED SUM OF "SQUARED" INDIVIDUAL RESIDUALS IS INFINITE MESSAGE ISSUED FROM ESTIMATION STEP AT INITIAL OBJ. FUNCTION EVALUATION when i removed subject 934 and 935 from the dataset, it still came up with the same error. I've even tried increasing the initial estimates. If anyone can help, it'll be much appreciated. thank you, Joannellyn the code is: IPRD=F IF (STDY.EQ.1) THEN Y=IPRD*EXP(EPS(1))+EPS(5) ENDIF IF (STDY.EQ.2) THEN Y=IPRD*EXP(EPS(2))+EPS(6) ENDIF IF (STDY.EQ.3) THEN Y=IPRD*EXP(EPS(3))+EPS(7) ENDIF IF (STDY.EQ.4) THEN Y=IPRD*EXP(EPS(4))+EPS(8) ENDIF $SIGMA BLOCK(1) 1 $SIGMA BLOCK(1) SAME $SIGMA BLOCK(1) 1 $SIGMA BLOCK(1) SAME $SIGMA 20 ; EPS(5) 1000 ; EPS(6) 1000 ; EPS(7) 1000 ; EPS(8) _______________________________________________________ From: "Serge Guzy" GUZY@xoma.com Subject: RE: [NMusers] Error when combining proportional residual error, Date: Wed, 2 Aug 2006 09:14:55 -0700 I think the problem is that you did not define really a combined proportional with additive but instead an exponential error + additive. Can you try to write instead IF (STDY.EQ.1) THEN Y=IPRD* (1+EPS(1)) +EPS(5) ENDIF IF (STDY.EQ.2) THEN Y=IPRD* (1+EPS(2)) +EPS(6) ENDIF IF (STDY.EQ.3) THEN Y=IPRD* (1+EPS(3)) +EPS(7) ENDIF IF (STDY.EQ.4) THEN Y=IPRD*(1+EPS(4)) +EPS(8) ENDIF In the MCPEM program for example, an exponential error variance does not really exist. When you assume exponential error variance, the data are log-transformed and the error model is then assumed to follow a constant variance model. In the MCPEM it does not make any sense to combine exponential with additive. I guess something similar is used with NONMEM. Serge Guzy President POP-PHARM _______________________________________________________ From: Leonid Gibiansky leonidg@metrumrg.com Subject: RE: [NMusers] Error when combining proportional residual error, Date: Wed, 02 Aug 2006 13:22:29 -0400 No, this is not the case with NONMEM. It is perfectly OK to combine exponential and additive errors. My guess is that STDY is not equal to 1, 2, 3, or 4 for some observation, or there exist some other model coding error that is difficult to find without seeing the entire code. To avoid STDY problem, try Y=IPRD*EXP(EPS(1))+EPS(5) IF (STDY.EQ.2) THEN Y=IPRD*EXP(EPS(2))+EPS(6) ENDIF IF (STDY.EQ.3) THEN Y=IPRD*EXP(EPS(3))+EPS(7) ENDIF IF (STDY.EQ.4) THEN Y=IPRD*EXP(EPS(4))+EPS(8) ENDIF Leonid _______________________________________________________ From: "Serge Guzy" GUZY@xoma.com Subject: RE: [NMusers] Error when combining proportional residual error, Date: Wed, 02 Aug 2006 Hi Leonid. When you use exponential error model, don't you think NONMEM transform your Concentration data into LogC??? If not, how do you compute the Log-Likelihood?? Of course I think in terms of MCPEM but I cannot understand how you can combine an exponential error with additive and compute a log-likelihood. More specifically, how do you compute the standard deviation that is needed in the computation of the log-likelihood? Log-likelihood= -log(sd)-((Cobs -CPREDICTED)/(SD))2/2 Serge _______________________________________________________ From: Leonid Gibiansky leonidg@metrumrg.com Subject: RE: [NMusers] Error when combining proportional residual error, Date: Wed, 02 Aug 2006 14:18:48 -0400 NONMEM does not transform data into the log form. As to the likelihood step evaluation, I think NONMEM uses Taylor expansion exp(eta)=1+eta effectively fitting the proportional rather than exponential error model. On the simulation step the exact exponential model is implemented. Leonid _______________________________________________________