Re: Standard error of 'secondary' parameters

Date: Mon, 15 Nov 1999 13:14:35 -0500 (EST) From: "Chuanpu Hu 301-827-3210 FAX 301-480-2825" <HUC@cder.fda.gov> Subject: Re: Standard error of 'secondary' parameters Looking at the SE's also has theoretical basis, and is termed the "Wald test" in statistics. In the case of nonlinear mixed effects modeling, both the Wald test and likelihood ratio test are asymptotic (approximate) tests. That is, theoretically the p-values become more accurate when sample sizes increase. The practical matter is which "asymptotics" kicks in earlier. The author of the S-Plus nonlinear mixed effects routine nlme claimed that, based on simulation results, the likelihood ratio test performs better with the fixed effect parameters (THETAs), and the Wald test performs better with the random effect parameters (OMEGAs). It should be interesting if someone would do a similar study in NONMEM. Chuanpu