Abstract:
:In this article, we present an estimation approach for solving nonlinear constrained generalized estimating equations that can be implemented using object-oriented software for nonlinear programming, such as nlminb in Splus or fmincon and lsqnonlin in Matlab. We show how standard estimating equation theory includes this method as a special case so that our estimates, when unconstrained, will remain consistent and asymptotically normal. To illustrate this method, we fit a nonlinear dose-response model with nonnegative mixed bound constraints to clustered binary data from a developmental toxicity study. Satisfactory confidence intervals are found using a nonparametric bootstrap method when a common correlation coefficient is assumed for all the dose groups and for some of the dose-specific groups.
journal_name
Biometricsjournal_title
Biometricsauthors
Contreras M,Ryan LMdoi
10.1111/j.0006-341x.2000.01268.xsubject
Has Abstractpub_date
2000-12-01 00:00:00pages
1268-71issue
4eissn
0006-341Xissn
1541-0420journal_volume
56pub_type
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