LOG(F) Error Model/Machine Differences

From luann@phor.com Fri Aug 23 10:36:40 1996 Subject: LOG(F) Error Model/Machine Differences NONMEM Users, We have recently been working with analyses requiring error models incorporating LOG(F). During this process, we discovered that this type of $ERROR model is handled differently for a DEC Alpha machine versus a SUN workstation. I have outlined the problem and the solution below. I've also included my interpretation of why the problem occurs and one exception for which the `solution' does not work (Many thanks, to Alison). I have been told that the VAX performs similar to the DEC. I have not heard how the MAINFRAME handles this error model. Luann /**************************************/ /* ERROR MODELS INVOLVING LOG(F) */ /**************************************/ PROBLEM: $ERROR Y=LOG(F) + EPS(1) or any other model with log(F) SUN: Will successfully complete the NONMEM run as it appears unless the data file contains concentrations prior to the first dose of drug. In the later case, NONMEM gives an INTRA-INDIVIDUAL VARIABILITY ESTIMATED TO BE ZERO error. DEC: Produces an immediate fortran error code of DIVIDE BY ZERO. SOLUTION: $ERROR FLAG=0 IF(AMT.NE.0) FLAG=1 Y=LOG(F+FLAG) + EPS(1) For dose records, Y=LOG(F+1) + EPS(1). For other records, Y=LOG(F) + EPS(1). WHY: For first dose records, NONMEM estimates F=0. For the error model Y=LOG(F)+EPS(1), this requires NONMEM to compute LOG(0) which is -infinity. Since the DEC FORTRAN compiler is set to disallow exceptional values(I believe this is the default), the run results in a FORTRAN error code. SUN FORTRAN compilers allow exceptional values and therefore the run is completed. Since the predicted Cp for DOSE records does NOT impact the fit of a model, the above code will allow both the DEC and the SUN to fit the LOG CP model. EXCEPTION: If NONMEM predicts a Cp of zero for a concentration record, the DEC and SUN will still result in the errors described above. If this occurs, the use of the LOG CP model should be revaluated or the problematic data records should be deleted from the analysis.