Weighted scores method for regression models with dependent data

Nikoloulopoulos, Aristidis K. ORCID: https://orcid.org/0000-0003-0853-0084, Joe, Harry and Chaganty, N. Rao (2011) Weighted scores method for regression models with dependent data. Biostatistics, 12 (4). pp. 653-665. ISSN 1468-4357

Full text not available from this repository.

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.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Statistics (former - to 2024) Faculty of Science > Research Groups > Numerical Simulation, Statistics & Data Science
Depositing User:	Michelle Harris
Date Deposited:	16 Mar 2011 09:59
Last Modified:	07 Nov 2024 12:32
URI:	https://ueaeprints.uea.ac.uk/id/eprint/26322
DOI:	10.1093/biostatistics/kxr005

Actions (login required)

View Item