From: Garry Boswell GBoswell@pcyc.com Subject: [NMusers] Constant and Proportional Error with Log transformed data with single data point per subject Date: Thu, May 20, 2004 6:53 pm NM Users, I have a PK study in mice in which I have a single blood sample per mouse, groups of 6 mice per time point. I have both IP and IV data from both single and multiple dose administration. During the model building process it appeared that an additive plus proportional error structure provided a better "fit" than other error structures. As noted by Ette et al (JPP 23(5), 1995) with only a single sample per animal I could not separately estimate interanimal and residual variability. Therefore I fixed Omega =0. Using the code below (error code suggested by Leonid Gibiansky in an earlier List Serve post), I was able to fit the non-log transformed data but the model was not adequate based on the diagnostic plots, etc. I was able to fit the log transformed data using Y=log(F)+Err(1) as described in NONMEM Tip #9. However I wanted to try the additive plus proportional error structure but with log transformed data. NONMEM Tips #9 and #10 nicely address the method of doing this with log transformed data but with what I believe is for data with multiple samples from each individual. My question is, can the methods described in these tips be applied to my model with Omega =0 FIXED? TIA for any assistance. Garry $PROB DRUG X PK STUDY $INPUT ID DAY=DROP TIME AMT MDV EVID DV LNDV WT SEX CMT SS II $DATA Dataset_04.csv IGNORE=# $SUBROUTINES ADVAN2 TRANS2 $PK TVCL = THETA(1) TVV = THETA(2) TVKA = THETA(3) TVF2 = THETA(4) CL =TVCL* EXP(ETA(1)) V =TVV KA=TVKA F2 =TVF2 K = CL/V HALF = (0.693/K) S2 = V $ERROR IPRED=F IRES=DV-IPRED IWRES=(DV-IPRED)/SQRT(F*F*THETA(1)*THETA(1)+THETA(2)*THETA(2) ) Y=F*(1+THETA(5)*EPS(1))+THETA(6)*EPS(2) $THETA (0, 15) $THETA (0, 10) $THETA (0, 0.8) $THETA (0, 0.7) $THETA (0, 0.5) $THETA (0, 0.01) $OMEGA 0 FIXED $SIGMA 1 FIXED $SIGMA 1 FIXED $EST MAXEVALS = 9900 NOABORT SIGDIGITS =3 PRINT =10 POSTHOC METHOD=CONDITIONAL $COV PRINT=E $TABLE NOPRINT ONEHEADER ID SEX TIME CL V KA F2 HALF WT FILE=Outfile_04.txt _______________________________________________________ From: Leonid Gibiansky lgibiansky@emmes.com Subject: RE:[NMusers] Constant and Proportional Error with Log transformed data with single data point per subject Date: Fri, May 21, 2004 9:35 am Garry, IWRES is computed incorrectly in your code (if it was similar in my post then I just mistyped it). There should be the same THETAs as in the error definition, i.e., IWRES=(DV-IPRED)/SQRT(F*F*THETA(5)*THETA(5)+ THETA(6)*THETA(6) ) You may use it with the log-transformed data as follows: >$ERROR >IPRED=F IF(IPRED.LT.0.1) IPRED=0.1 ; use something small here, like LOQ/2 in place of 0.1 W = SQRT( (THETA(5)/IPRED)**2 +THETA(6) ) Y= LOG(IPRED)+W*EPS(1) >IRES=DV-LOG(IPRED) >IWRES=IRES/W $SIGMA 1 FIXED This is based on the posting by Mats Karlsson as of Mon, 29 Apr 2002 (99apr232002.html), I copied it below: Mats Karlsson wrote on Mon, 29 Apr 2002: Hi, To get the same error structure for log-transformed data as the additive+proportional on the normal scale, I use Y=LOG(F)+SQRT(THETA(x)**2+THETA(y)**2/F**2)*EPS(1) with $SIGMA 1 FIX THETA(x) and THETA(y) will have the same meaning as on the untransformed scale with Y=F+SQRT(THETA(y)**2+THETA(x)**2*F**2)*EPS(1) with $SIGMA 1 FIX .... cut here ===================================== _______________________________________________________