Logo
DeutschClear Cookie - decide language by browser settings
Kastner, C. and Ziegler, Andreas (1999): A Comparison of Jackknife Estimators of Variance for GEE2. Collaborative Research Center 386, Discussion Paper 167
[img]
Preview

PDF

257kB

Abstract

Marginal regression modeling with generalised estimating equations became very popular in the last decade. While the mean structure is of primary interest in first-order generalised estimating equations (GEE1), second-order generalised estimating equations (GEE2) allow the estimation of both the mean and the association structure. It has repeatedly been shown that the usual robust variance estimator for the GEE1 is conservative, especially in small samples. As an alternative, the jackknife estimator of variance can be used. In this discussion paper, we extend the different jackknife estimators of variance to GEE2 models. The variance estimators are compared in a simulation study. While there is only little difference in the variance estimates of the mean structure across simulated models, the results differ substantially with respect to the association structure. The fully iterated jackknife estimator seems to be the most appropriate when focusing on the GEE2.