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On the use of repeated measurement errors in linear regression models

Author

Listed:
  • Mengli Zhang

    (Shanghai University of Finance and Economics)

  • Yang Bai

    (Shanghai University of Finance and Economics)

Abstract

In a linear mean regression setting with repeated measurement errors, we develop asymptotic properties of a naive estimator to better clarify the effects of these errors. We then construct a group of unbiased estimating equations with independent repetitions and make use of these equations in two ways to obtain two estimators: a weighted averaging estimator and an estimator based on the generalized method of moments. The proposed estimators do not require any additional information about the measurement errors. We also prove the consistency and asymptotic normality of the two estimators. Our theoretical results are verified by simulation studies and a real data analysis.

Suggested Citation

  • Mengli Zhang & Yang Bai, 2021. "On the use of repeated measurement errors in linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 779-803, July.
  • Handle: RePEc:spr:metrik:v:84:y:2021:i:5:d:10.1007_s00184-020-00801-2
    DOI: 10.1007/s00184-020-00801-2
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    References listed on IDEAS

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    1. Chan, Lai K. & Mak, Tak K., 1979. "On the Maximum Likelihood estimation of a linear structural relationship when the intercept is known," Journal of Multivariate Analysis, Elsevier, vol. 9(2), pages 304-313, June.
    2. Da Silva, Damião Nóbrega & Skinner, Chris J. & Kim, Jae Kwang, 2016. "Using binary paradata to correct for measurement error in survey data analysis," LSE Research Online Documents on Economics 64763, London School of Economics and Political Science, LSE Library.
    3. Chen, Xiaohong & Jacho-Chávez, David T. & Linton, Oliver, 2016. "Averaging Of An Increasing Number Of Moment Condition Estimators," Econometric Theory, Cambridge University Press, vol. 32(1), pages 30-70, February.
    4. Laurence S. Freedman & Vitaly Fainberg & Victor Kipnis & Douglas Midthune & Raymond J. Carroll, 2004. "A New Method for Dealing with Measurement Error in Explanatory Variables of Regression Models," Biometrics, The International Biometric Society, vol. 60(1), pages 172-181, March.
    5. Liang, Hua & Zou, Guohua & Wan, Alan T. K. & Zhang, Xinyu, 2011. "Optimal Weight Choice for Frequentist Model Average Estimators," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 1053-1066.
    6. Grace Y. Yi & Yanyuan Ma & Raymond J. Carroll, 2012. "A functional generalized method of moments approach for longitudinal studies with missing responses and covariate measurement error," Biometrika, Biometrika Trust, vol. 99(1), pages 151-165.
    7. Jin-Guan Lin & Chun-Zheng Cao, 2013. "On estimation of measurement error models with replication under heavy-tailed distributions," Computational Statistics, Springer, vol. 28(2), pages 809-829, April.
    8. Jeffrey R. Thompson & Randy L. Carter, 2007. "An Overview of Normal Theory Structural Measurement Error Models," International Statistical Review, International Statistical Institute, vol. 75(2), pages 183-198, August.
    9. Qin, Guoyou & Zhang, Jiajia & Zhu, Zhongyi, 2016. "Simultaneous mean and covariance estimation of partially linear models for longitudinal data with missing responses and covariate measurement error," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 24-39.
    10. Damião Nóbrega Da Silva & Chris Skinner & Jae Kwang Kim, 2016. "Using Binary Paradata to Correct for Measurement Error in Survey Data Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 526-537, April.
    11. S. D. Hodges & P. G. Moore, 1972. "Data Uncertainties and Least Squares Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 185-195, June.
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