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SIMEX estimation in case of correlated measurement errors

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Abstract

The simulation-extrapolation (SIMEX) approach of Cook and Stefanski (J. Am. Stat. Assoc. 89:1314–1328, 1994) has proved to be successful in obtaining reliable estimates if variables are measured with (additive) errors. In particular for nonlinear models, this approach has advantages compared to other procedures such as the instrumental variable approach if only variables measured with error are available. However, it has always been assumed that measurement errors for the dependent variable are not correlated with those related to the explanatory variables although such scenario is quite likely. In such a case the (standard) SIMEX suffers from misspecification even for the simple linear regression model. Our paper reports first results from a generalized SIMEX (GSIMEX) approach which takes account of this correlation. We also demonstrate in our simulation study that neglect of the correlation will lead to estimates which may be worse than those from the naive estimator which completely disregards measurement errors.

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Authors and Affiliations

  1. Wirtschaftswissenschaftliche Fakultät, Universität Tübingen, Mohlstrasse 36, 72074, Tübingen, Germany

    Gerd Ronning

  2. Institute for Applied Research (IAW), Ob dem Himmelreich 1, 72074, Tübingen, Germany

    Martin Rosemann

Authors
  1. Gerd Ronning
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  2. Martin Rosemann
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Correspondence to Gerd Ronning.

Additional information

Results in this paper are related to the project “Wirtschaftsstatistische Paneldaten und faktische Anonymisierung,” which is financed by Bundesministerium für Bildung und Forschung. We thank Olaf Hübler and Sandra Nolte for hints on relevant publications and Helmut Küchenhoff and Hans Schneeweiß for helpful comments on an earlier version. We also thank the two anonymous referees for their critical remarks.

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Ronning, G., Rosemann, M. SIMEX estimation in case of correlated measurement errors. AStA Adv Stat Anal 92, 391–404 (2008). https://doi.org/10.1007/s10182-008-0086-x

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  • DOI: https://doi.org/10.1007/s10182-008-0086-x

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