Re: When to do transformation of data?

From: Leonid Gibiansky Subject: Re: [NMusers] When to do transformation of data? Date: Tue, 23 Apr 2002 09:16:52 -0400 I had an example recently where I exhausted all my options in improving the model, and it still was not good enough (FO was giving too high estimates for omegas and biased PRED vs. DV plots, FOCE with interaction OF was strongly dependent on the number of significant digits that I requested and on the initial guess). Then I was advised to do log-transformation for DV, and it worked like a miracle and stabilized the model. The main thing (at least, on the paper, I am not so sure about internal details of the NONMEM algorithm; any thoughts why it could be so helpful ?) is to provide true exponential error model: ln(Y)=ln(F) + EPS is equivalent to Y=F EXP(EPS) whereas Y=F EXP(EPS) is approximated by NONMEM as Y=F(1+EPS) So if EPS (SIGMA) is large enough, EXP(EPS) is not equal to (1+EPS), and the log-transformed approximation could be better. On the other hand, I do not know how to code the error model Y=F*exp(EPS1) + EPS2 in log-transformed variables. Any advices on this one ? Thanks, Leonid