Log normal data

From: alison@c255.ucsf.EDU (ABoeckmann) Subject: Log normal data Date: 29 Oct 1997 18:57:02 -0500 Re: David Nix's email, Stuart Beal offers these remarks. >Is there any way to force NONMEM to use a log-normal distribution for >the intersubject variability involving PK parameters? Use the exponential model for the PK parameters and FOCE. >The only way that I can come up with is to: > > 1. Enter concentration data as log transformed values > DV=LN (conc) > 2. Model Y=Log(F) + EPS(1) > >Is this valid? This is a valid and useful way to handle intrasubject variability, not intersubject variability (you seem to be asking about the latter with your first question). >Is there any way to evaluate whether a log-normal or normal >distribution provides the best goodness of fit for a given data set >within NONMEM? To compare goodness of fit results between any two models, plot DV vs. PRED for both models on the same scale and see how they look. You are right, objective functions from two analyses, one using the observations and the other using the log-transformed observations, cannot be compared. NONMEM doesn't make distributional assumptions per se. Still, if the "individual analysis" is more or less as you say, one would want to do something to reflect this. As stated above, use the exponential model and FOCE.