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The Stata Journal
Volume 3 Number 4: pp. 342-350

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Variance estimation for the instrumental variables approach to measurement error in generalized linear models

James W. Hardin
Arnold School of Public Health
University of South Carolina
Columbia, SC 29208
Raymond J. Carroll
Department of Statistics MS-3143
Texas A&M University
College Station, TX 77843-3143
Abstract.   This paper derives and gives explicit formulas for a derived sandwich variance estimate. This variance estimate is appropriate for generalized linear additive measurement error models fitted using instrumental variables. We also generalize the known results for linear regression. As such, this article explains the theoretical justification for the sandwich estimate of variance utilized in the software for measurement error developed under the Small Business Innovation Research Grant (SBIR) by StataCorp. The results admit estimation of variance matrices for measurement error models where there is an instrument for the unknown covariate.
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View all articles with these keywords: sandwich estimate of variance, measurement error, White's estimator, robust variance, generalized linear models, instrumental variables

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