IDEAS home Printed from https://ideas.repec.org/p/qsh/wpaper/161326.html

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://gking.harvard.edu//node/161326
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Meyer, Bruce D. & Mittag, Nikolas & Wu, Derek, 2024. "Race, Ethnicity, and Measurement Error," IZA Discussion Papers 17349, Institute of Labor Economics (IZA).
    2. 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.
    3. 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, pages 327-381, National Bureau of Economic Research, Inc.
    4. Gazmararian, Alexander F., 2024. "Valuing the Future: Changing Time Horizons and Policy Preferences," OSF Preprints 2m9fy, Center for Open Science.
    5. 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.
    6. Christian Aßmann & Jean-Christoph Gaasch & Doris Stingl, 2023. "A Bayesian Approach Towards Missing Covariate Data in Multilevel Latent Regression Models," Psychometrika, Springer;The Psychometric Society, vol. 88(4), pages 1495-1528, December.
    7. Edmund Malesky & Markus Taussig, 2019. "How Do Firms Feel About Participation by Their Peers in the Regulatory Design Process? An Online Survey Experiment Testing the Substantive Change and Spillover Mechanisms," Strategy Science, INFORMS, vol. 4(2), pages 129-150, June.
    8. 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.
    9. Raghul Gandhi Venkatesan & Bagavandas Mappillairaju, 2024. "Early student dropout detection in Indian secondary education with special reference to selected districts in Tamil Nadu: a machine learning-based survival analysis approach," Journal of Computational Social Science, Springer, vol. 7(3), pages 2309-2331, December.
    10. 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).
    11. Joscha Legewie, 2018. "Living on the Edge: Neighborhood Boundaries and the Spatial Dynamics of Violent Crime," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1957-1977, October.
    12. 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.
    13. repec:osf:osfxxx:2m9fy_v1 is not listed on IDEAS
    14. Brander, Michael & Bernauer, Thomas & Huss, Matthias, 2021. "Improved on-farm storage reduces seasonal food insecurity of smallholder farmer households – Evidence from a randomized control trial in Tanzania," Food Policy, Elsevier, vol. 98(C).
    15. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    16. 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).
    17. 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.
    18. 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.
    19. Joseph T. Ripberger & Hank C. Jenkins‐Smith & Carol L. Silva & Jeffrey Czajkowski & Howard Kunreuther & Kevin M. Simmons, 2018. "Tornado Damage Mitigation: Homeowner Support for Enhanced Building Codes in Oklahoma," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2300-2317, November.
    20. Samira Rousselière & Thomas Coisnon & Mahmoud Hassan & Anne Musson & Damien Rousselière, 2024. "Beyond Porter hypothesis : Empirical evidence of heterogeneous and contextual economic returns of eco-innovations on a sample of European SMEs," Post-Print hal-04810500, HAL.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qsh:wpaper:161326. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Richard Brandon The email address of this maintainer does not seem to be valid anymore. Please ask Richard Brandon to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/cbrssus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.