Re: Analysis of sparse data

Date: Mon, 19 Jul 1999 13:04:18 -0700 From: LSheiner <lewis@c255.ucsf.edu> Subject: Re: Analysis of sparse data Joining the data sets (if you think the populations are the same) is the right thing to do. Interindividual variability cannot in general be estimated from data sets unless a significant number of individuals have at least as many observations as there are distinct parameters in the individual model. There has been considerable simulation work verifying this. In your case, the 2 populations are not necesarily the same (normals vs patients). The estimates you get are then some hybrid of the approriate values for the 2 populations (which, of course, are not necessarily different, regarding PK). The only alternative to merging the data sets is using a prior distribution on the popualtion paramters, notably the elements of OMEGA. Unfortunately, the NONMEM feature allowing you to do this conveniently is not part of the currently distributed verion. LBS. Lewis B Sheiner, MD Professor: Lab. Med., Biopharm. Sci., Med. Box 0626 voice: 415 476 1965 UCSF, SF, CA fax: 415 476 2796 94143-0626 email: lewis@c255.ucsf.edu