Comaprison of two models

Dear NMusers I would like to compare two models. Let’s say the model M1 and the model M2. The model M1 is a simple one with just one observation compartment (Y = IPRE*(1+ERR)). The second one is a more complex one with three observation compartments (Y1 = IPRE1*(1+ERR1); Y2=IPRE2*(1+ERR2); Y3=IPRE3*(1+ERR3)). The data sets are identical with regards to the first observation compartment. Y form M1 is in fact Y1 from M2 and Y2 and Y3 from M2 are additional observations which should improve the model because of additional information or perhaps not because of additional noise. If I am interested in comparing the two models focusing on the first observation (i.e. Y form M1 and Y1 form M2, respectively), I cannot use the OFV, since OFV2 (OFV for M2) will be a global measure of the fit including Y2 and Y3 from M2. So, how can I perform an estimation of M2 including the three observations and then isolate the contribution of Y1 to the global OFV2? May I assume additional properties of OFV, i.e. OFTtotal = OFV1+OFV2+OFV3? Is it possible to code the model so that only OFV1 will be computed? Many thanks in advance. Let me know if you need additional information. Best regards Robert ___________________________________________ Robert M. Kalicki, MD Postdoctoral Fellow Department of Nephrology and Hypertension Inselspital University of Bern Switzerland Address: Klinik und Poliklinik für Nephrologie und Hypertonie KiKl G6 Freiburgstrasse 15 CH-3010 Inselspital Bern Tel +41(0)31 632 96 63 Fax +41(0)31 632 14 58