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Kukush, Alexander
Schneeweiss, Hans
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Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 477
we prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiased) linear score estimators, in the sense that the difference of the asymptotic covariance matrices of the linear score and quasi-score estimator is positive semi-definite. We also give conditions under which this difference in zero or under which it is positive definite. This result can be applied to measurement error models where it implies that the quasi-score estimator is asymptotically more efficient than the corrected score estimator.
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