Fitting nonlinear and constrained generalized estimating equations with optimization software.

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

Biometrics

journal_title

Biometrics

authors

Contreras M,Ryan LM

doi

10.1111/j.0006-341x.2000.01268.x

subject

Has Abstract

pub_date

2000-12-01 00:00:00

pages

1268-71

issue

4

eissn

0006-341X

issn

1541-0420

journal_volume

56

pub_type

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