A bias-corrected covariance estimator for improved inference when using an unstructured correlation with quadratic inference functions

被引：5

作者：

Westgate, Philip M. ^{[1
]}

机构：

[1] Univ Kentucky, Coll Publ Hlth, Dept Biostat, Lexington, KY 40536 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2013年 / 83卷 / 06期

关键词：

Correlated data; Efficiency; Generalized estimating equations; Marginal model; Working correlation structure; ESTIMATING EQUATIONS;

D O I：

10.1016/j.spl.2013.02.021

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Notable bias can exist in the empirical covariance matrix of parameter estimates obtained from the quadratic inference function method that incorporates an unstructured working correlation. We therefore derive a bias correction. Via simulation, we show that the proposed correction leads to appropriate standard error estimation. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：1553 / 1558

页数：6

共 39 条

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[J]. STATISTICS IN MEDICINE, 2013, 32 (16) : 2850 - 2858

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