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

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.


Issue Date:
2003
Publication Type:
Journal Article
DOI and Other Identifiers:
st0048 (Other)
PURL Identifier:
http://purl.umn.edu/116177
Published in:
Stata Journal, Volume 03, Number 4
Page range:
342-350
Total Pages:
9

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 Record created 2017-04-01, last modified 2017-08-26

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