Document Type

Article

Publication Date

2011

DOI

10.1093/biostatistics/kxr005

Publication Title

Biostatistics

Volume

12

Issue

4

Pages

653-665

Abstract

There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our method is robust and nearly as efficient as maximum likelihood for fully specified copula models. An illustrative example is given to show the use of our weighted scores method to analyze utilization of health care based on family characteristics.

Comments

Web of Science: "Free full-text from publisher -- gold open access."

Original Publication Citation

Nikoloulopoulos, A. K., Joe, H., & Chaganty, N. R. (2011). Weighted scores method for regression models with dependent data. Biostatistics, 12(4), 653-665. doi:10.1093/biostatistics/kxr005

Download

Share

COinS