Modeling the Association Structure in Doubly Robust GEE for Longitudinal Ordinal Missing Data

• Main Authors: da Silva, José Luiz P, Colosimo, Enrico A, Demarqui, Fábio N
• Format: Journal Article
• Language: English
• Published: 14-06-2015
• Subjects: Statistics - Methodology
• DOI: 10.48550/arxiv.1506.04452

Generalized Estimation Equations (GEE) are a well-known method for the
analysis of categorical longitudinal responses. GEE method has computational
simplicity and population parameter interpretation. In the presence of missing
data it is only valid under the strong assumption of missing completely at
random. A doubly robust estimator (DRGEE) for correlated ordinal longitudinal
data is a nice approach for handling intermittently missing response and
covariate under the MAR mechanism. Independent working correlation is the
standard way in DRGEE. However, when covariate is not time stationary,
efficiency can be gained using a structured association. The goal of this paper
is to extend the DRGEE estimator to allow modeling the association structure by
means of either the correlation coefficient or local odds ratio. Simulation
results revealed better performance of the local odds ratio parametrization,
specially for small samples. The method is applied to a data set related to
Rheumatic Mitral Stenosis.