Re: Problems with an apparent compiler-senstive model

From: Mark Sale - Next Level Solutions mark@nextlevelsolns.com Subject: Re: [NMusers] Problems with an apparent compiler-senstive model Date: Thu, 03 Aug 2006 06:57:53 -0700 At the risk of annoying the majority of people on this user group, a few more comments. I think we need to step back even farther and ask the critial question - We are looking for usefulness - not correctness. So, what is the model to be used for? Increasingly - in fact almost exclusively in my recent experience, we want to simulate from these models - and in fact extrapolate the models. We extrapolate accross dose (higher doses), duration (longer), populations (older, younger) and even diseases - sometimes even species. If we want to extrapolate/simulate, why would we care about statistical properties of a model (like the conditioning number/rank of the variance matrix). What we should care (mostly) about is: 1. Is the model biologically plausible? 2. Are simulations from the model consistent with observed data? (predicitive check|posterior predicitive check). If you want to test/generate hypotheses, then this doesn't apply, but I actually haven't done that in some time. For hypothesis testing, we do need to live in the world of statistics. But, in fact, statistics do matter if you want to extrapolate/simulate. It is easy to show that an overparameterized model is dangerous to extrapolate, even if it is entirely consistent with the data from which it was derived. So, back to my point: For extraploation/simulation (and the two go together, why would you bother simualted data that you already have real data for?) my first priorities are biological plausability and predicitive checks, as well as reality checks for extrapolations. But, I'd also really, really like to to converge, and I'd like it to do a covariance step as well. However, with enough testing, I can live without convergence - I can't live with a biologically implausible model (you need to either change the model or rethink the biology), or a model that cannot reproduce the data from which it is derived. Mark Sale MD Next Level Solutions, LLC www.NextLevelSolns.com