title: Approximate testing in two-stage nonlinear mixed models.
abstract: We investigate here small sample properties of approximateF-tests about fixed effects parameters in nonlinear mixed models. For estimation of population fixed effects parameters as well as variance components, we apply the two-stage approach. This method is useful and popular when the number of observations per sampling unit is large enough. The approximateF-test is constructed based on large sample approximation to the distribution of nonlinear least squares estimates of subject-specific parameters. We recommend a modified test statistic that takes into consideration approximation to the large sample Fisher information matrix (See [1]). Our main focus is on comparing finite sample properties of broadly used approximate tests (Wald test and likelihood ratio test) and the modifiedF-test under the null hypothesis, especially accuracy ofp-values (See [2]). For that purpose two extensive simulation studies are conducted based on pharmacokinetic models (See [3, 4]).
authors.affiliation: Pennington Biomedical Research Center, LSU, Baton Rouge, LA, USA;
authors.forename: J H
authors.initials: JH
authors.lastname: Burton
authors.affiliation: LSUHSC School of Public Health, New Orleans, LA, USA;
authors.forename: J
authors.initials: J
authors.lastname: Volaufova
keywords: Two-stage nonlinear mixed model; accuracy of p-value; approximate test