RE: Parameterization!!!

From: "Gibiansky, Leonid" <gibianskyl@globomax.com> Subject: RE: Parameterization!!! Date: Fri, 11 May 2001 08:29:58 -0400 Dear Mats, As you mentioned, the model CL=THETA(1)*EXP(ETA(1)+ETA(3)) V=THETA(2)*EXP(ETA(2)+ETA(3)) imposes restrictions on the covariate matrix. For example, the models with negative correlations CL=THETA(1)*EXP(ETA(1)+ETA(3)) V=THETA(2)*EXP(ETA(2)-ETA(3)) are not covered. More general (and the most general) one would be CL=THETA(1)*EXP(ETA(1)+ETA(3)) V=THETA(2)*EXP(ETA(2)+THETA(3)*ETA(3)) However, with this model one has an extra parameter, and it may cause problems on the covariance and/or POSTHOC steps (have you tried it ? is it really a problem ?). Alternatively, one can try CL=THETA(1)*EXP(ETA(1)) V=THETA(2)*EXP(ETA(2)+THETA(3)*ETA(1)) In this case, ETA(1) is mainly responsible for the covariates present in CL, THETA(3) shows the correlation, and ETA(2) is mainly responsible for the covariates that are present only in V. Plots of ETA(1) and ETA(2) vs. covariates then will show what to include into covariate model for each of the parameters. Do you have any experience with similar parameterizations ? Thanks, Leonid