RE: GAM analysis and further action

From: "Jakob Ribbing" Jakob.Ribbing@farmbio.uu.se Subject: RE: [NMusers] GAM analysis and further action Date: Wed, 29 Mar 2006 21:03:07 +0200 Dear Toufigh, AIC=chi2 2 * #covariate-parameters If you would use the AIC criterion for model selection within NONMEM then deltaAIC = deltaOFV 2 * delta#parameters. However, you would not get the same results, partly because the empirical-bayes estimates (individual eta or delta-parameters=CLi-TVCL) used in the GAM are shrunk towards the population mean (the NONMEM model that you fit assumes that CL is independent of any covariates)[1]. As Mats pointed out, fitting the model in NONMEM would therefore be a good idea, after selecting a set of covariates to test, which are not highly correlated and which are biologically plausible (unless large dataset). As for letting the data decide the functional form to test, this would also require many individuals (unless you follow the individuals from very young until kindergarten :>) You may also try looking at delta-parameters rather than etas to see the actual (but shrunk) relations between parameter and covariate. Best regards, Jakob 1. Wahlby, U., E.N. Jonsson, and M.O. Karlsson, Comparison of stepwise covariate model building strategies in population pharmacokinetic-pharmacodynamic analysis. AAPS PharmSci, 2002. 4(4): p. 27.