RE: General question on modeling

Mark > I've lately been reviewing the literature on model > building/selection algorithms. I have been unable to find > any even remotely rigorous discussion of the way we all build > NONMEM models. The structural first, then variances/forward > addition/backward elimination is generally mentioned in a > number of places I sort of hope that there is no prescriptive approach to model building for nonlinear mixed effects models since this would suggest that if you follow a set recipe you will end up with a model that works everytime. I'm sure everyone has anecdotes where a "nonlinear" approach to model building worked best, e.g. adding covariates prior to completion of building the structural PK model as is sometimes necessary to be able to build an adequate structural model. Surely the idea is to let the sciences of biological systems and statistics inform the modeller on how to best go about making their model (I have even heard some refer to this as the "art" of model building :-) ). Afterall if we believe that all models are wrong then all we really want from our model is one that performs well for the inference we wish to draw from it. Steve -- Professor Stephen Duffull Chair of Clinical Pharmacy School of Pharmacy University of Otago PO Box 913 Dunedin New Zealand E: [EMAIL PROTECTED] P: +64 3 479 5044 F: +64 3 479 7034 Design software: www.winpopt.com