Re: Bayesian estimation

From: Lewis B Sheiner <lewis@c255.ucsf.edu> Subject: Re: Bayesian estimation Date: Fri, 29 Sep 2000 09:43:40 -0700 Joga is addressing a more subtle issue than I believe Dr. Ho-Nguyen intended. An adequate answer to the original question is the one Alison previously provided: put the "initial estimates" of all parameters to the estimates from pop1, and then run pop2 data with $EST MAXEVAL=0 POSTHOC This produces a Bayes estimate for each individual in pop2 CONDITIONAL on the model estimated from pop1 (i.e., as though pop1 was infinite and so the fitted model is the "true" model). Joga's code, which involves an unsupported feature of NONMEM, and hence will not work with NONMEM V, attempts to find a Bayes estimate for the pop2 individuals that is unconditional; that is one which recognizes that the best fitting model to pop1 is not necessarily the "true" model. Note that the usual posthoc estimates, for example those for pop1 obtained as part of the run that fit the model to pop1, are of the conditional type, not of the unconditional type. For consistency, then, it might be preferable to use the simpler approach, or to use the more complex approach on both pop1 and pop2 ... As I said at the outset, this is a subtle issue, and if all that is rerquired is a reasonable set of estimates of the individual parameters in pop2, the simpler approach of conditioning on the model should suffice. LBS. -- _/ _/ _/_/ _/_/_/ _/_/_/ Lewis B Sheiner, MD (lewis@c255.ucsf.edu) _/ _/ _/ _/_ _/_/ Professor: Lab. Med., Biophmct. Sci., Med. _/ _/ _/ _/ _/ Box 0626, UCSF, SF, CA, 94143-0626 _/_/ _/_/ _/_/_/ _/ 415-476-1965 (v), 415-476-2796 (fax)