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A Unified Approach to Measurement Error and Missing Data: Details and Extensions

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  • Matthew Blackwell
  • James Honaker
  • Gary King

Abstract

We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model specifications and estimation procedures, and analyses to assess the approach?s robustness to correlated measurement errors and to errors in categorical variables. These results support using the technique to reduce bias and increase efficiency in a wide variety of empirical research.

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  • Matthew Blackwell & James Honaker & Gary King, "undated". "A Unified Approach to Measurement Error and Missing Data: Details and Extensions," Working Paper 161326, Harvard University OpenScholar.
    • Handle: RePEc:qsh:wpaper:161326
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    File URL: http://gking.harvard.edu//node/161326
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    References listed on IDEAS

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    1. Jonathan N. Katz & Gabriel Katz, 2010. "Correcting for Survey Misreports Using Auxiliary Information with an Application to Estimating Turnout," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 815-835, July.
    2. King, Gary & Honaker, James & Joseph, Anne & Scheve, Kenneth, 2001. "Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation," American Political Science Review, Cambridge University Press, vol. 95(1), pages 49-69, March.
    3. Matthew Blackwell & James Honaker & Gary King, 2017. "A Unified Approach to Measurement Error and Missing Data: Overview and Applications," Sociological Methods & Research, , vol. 46(3), pages 303-341, August.
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    2. S. Yang & J. K. Kim, 2016. "A note on multiple imputation for method of moments estimation," Biometrika, Biometrika Trust, vol. 103(1), pages 244-251.
    3. Marcus Groß, 2016. "Modeling body height in prehistory using a spatio-temporal Bayesian errors-in variables model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(3), pages 289-311, July.
    4. Bruce D. Meyer & Nikolas Mittag & Derek Wu, 2024. "Race, Ethnicity, and Measurement Error," NBER Chapters, in: Race, Ethnicity, and Economic Statistics for the 21st Century, National Bureau of Economic Research, Inc.
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    6. Gazmararian, Alexander F., 2024. "Valuing the Future: Changing Time Horizons and Policy Preferences," OSF Preprints 2m9fy, Center for Open Science.
    7. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    8. Matthew Blackwell & James Honaker & Gary King, 2017. "A Unified Approach to Measurement Error and Missing Data: Overview and Applications," Sociological Methods & Research, , vol. 46(3), pages 303-341, August.
    9. Kuwayama, Yusuke & Olmstead, Sheila & Zheng, Jiameng, 2022. "A more comprehensive estimate of the value of water quality," Journal of Public Economics, Elsevier, vol. 207(C).
    10. Simon Grund & Oliver Lüdtke & Alexander Robitzsch, 2021. "On the Treatment of Missing Data in Background Questionnaires in Educational Large-Scale Assessments: An Evaluation of Different Procedures," Journal of Educational and Behavioral Statistics, , vol. 46(4), pages 430-465, August.
    11. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.
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    14. Bruce D. Meyer & Nikolas Mittag, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," NBER Working Papers 25738, National Bureau of Economic Research, Inc.
    15. Rousselière, Damien & Bouchard, Marie J. & Rousselière, Samira, 2024. "How does the social economy contribute to social and environmental innovation? Evidence of direct and indirect effects from a European survey," Research Policy, Elsevier, vol. 53(5).

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