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This article explores, for a set of survey conditions, the effect of correlated measurement error on the ordinary least squares estimator of the regression coefficient for a finite bivariate population, when both variables are subject to correlated measurement error. The sample estimates for some selected housing variables show that the average of the correlated measurement error components have little effect, but the simple response variance and covariance have pronounced effect, on the ordinary regression estimator. In particular, the estimates of the simple response covariance studied are far from negligible. Finally, the article examines the sensitivity of the bias factor of the estimator.
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John J. Chai (1971) studied this question.
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