IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0286680.html
   My bibliography  Save this article

Generalized measurement error: Intrinsic and incidental measurement error

Author

Listed:
  • Edward Kroc

Abstract

In this paper, we generalize the notion of measurement error on deterministic sample datasets to accommodate sample data that are random-variable-valued. This leads to the formulation of two distinct kinds of measurement error: intrinsic measurement error, and incidental measurement error. Incidental measurement error will be recognized as the traditional kind that arises from a set of deterministic sample measurements, and upon which the traditional measurement error modelling literature is based, while intrinsic measurement error reflects some subjective quality of either the measurement tool or the measurand itself. We define calibrating conditions that generalize common and classical types of measurement error models to this broader measurement domain, and explain how the notion of generalized Berkson error in particular mathematicizes what it means to be an expert assessor or rater for a measurement process. We then explore how classical point estimation, inference, and likelihood theory can be generalized to accommodate sample data composed of generic random-variable-valued measurements.

Suggested Citation

  • Edward Kroc, 2023. "Generalized measurement error: Intrinsic and incidental measurement error," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-41, June.
    • Handle: RePEc:plo:pone00:0286680
    DOI: 10.1371/journal.pone.0286680
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0286680
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0286680&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0286680?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Manit Mishra, 2016. "Confirmatory Factor Analysis (CFA) as an Analytical Technique to Assess Measurement Error in Survey Research," Paradigm, , vol. 20(2), pages 97-112, December.
    2. Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
    3. Brownstone, David & Velletta, Robert G., 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," University of California Transportation Center, Working Papers qt2t08s22q, University of California Transportation Center.
    4. Edward Kroc, 2020. "Measurement protocols, random-variable-valued measurements, and response process error: Estimation and inference when sample data are not deterministic," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-25, October.
    5. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    6. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," University of California Transportation Center, Working Papers qt3gb0k9b5, University of California Transportation Center.
    7. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 705-717, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
    2. Rodolphe Desbordes & Gary Koop, 2014. "The Known Unknowns of Governance," Working Paper series 38_14, Rimini Centre for Economic Analysis.
    3. Pina-Sánchez Jose & Koskinen Johan & Plewis Ian, 2019. "Adjusting for Measurement Error in Retrospectively Reported Work Histories: An Analysis Using Swedish Register Data," Journal of Official Statistics, Sciendo, vol. 35(1), pages 203-229, March.
    4. Suziedelyte, Agne & Johar, Meliyanni, 2013. "Can you trust survey responses? Evidence using objective health measures," Economics Letters, Elsevier, vol. 121(2), pages 163-166.
    5. Mauro Mastrogiacomo, 2010. "Testing Consumers' Asymmetric Perception Of Changes In Household Financial Situation," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(2), pages 327-350, June.
    6. Javier Escobal & Sonia Laszlo, 2008. "Measurement Error in Access to Markets," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 209-243, April.
    7. Erik Meijer & Lynn A. Karoly & Pierre-Carl Michaud, 2010. "Using Matched Survey and Administrative Data to Estimate Eligibility for the Medicare Part D Low Income Subsidy Program," Working Papers WR-743, RAND Corporation.
    8. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
    9. Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
    10. Schrapler, Jorg-Peter, 2003. "Respondent behaviour in panel studies: a case study for income-nonresponse by means of the British Household Panel Study (BHPS)," ISER Working Paper Series 2003-08, Institute for Social and Economic Research.
    11. Donal O'Neill, 2015. "Correcting for Self-Reporting Bias in BMI: A Multiple Imputation Approach," Economics Department Working Paper Series n263-15.pdf, Department of Economics, National University of Ireland - Maynooth.
    12. Jörg-Peter Schräpler, 2002. "Respondent Behavior in Panel Studies: A Case Study for Income-Nonresponse by Means of the German Socio-Economic Panel (GSOEP)," Discussion Papers of DIW Berlin 299, DIW Berlin, German Institute for Economic Research.
    13. Marsh, L.C.Lawrence C., 2004. "The econometrics of higher education: editor's view," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 1-18.
    14. Jörg-Peter Schräpler, 2004. "Respondent Behavior in Panel Studies," Sociological Methods & Research, , vol. 33(1), pages 118-156, August.
    15. Riandy Laksono & Arianto A. Patunru, 2024. "The dynamics of labor share decline in manufacturing: Evidence from Indonesia," Departmental Working Papers 2024-3, The Australian National University, Arndt-Corden Department of Economics.
    16. Rehkopf, David H. & Jencks, Christopher & Glymour, M. Maria, 2010. "The association of earnings with health in middle age: Do self-reported earnings for the previous year tell the whole story?," Social Science & Medicine, Elsevier, vol. 71(3), pages 431-439, August.
    17. Emre Ekinci, 2009. "Dealing with Attrition When Refreshment Samples are Available: An Application to the Turkish Household Labor Force Survey," 2009 Meeting Papers 353, Society for Economic Dynamics.
    18. Chris Skinner & Nigel Stuttard & Gabriele Beissel‐Durrant & James Jenkins, 2002. "The Measurement of Low Pay in the UK Labour Force Survey," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(supplemen), pages 653-676, December.
    19. Martin Schmalz & Jean-François Kagy & Jose Azar, 2014. "Can Changes in the Cost of Cash Resolve the Corporate Cash Puzzle?," 2014 Meeting Papers 1027, Society for Economic Dynamics.
    20. Fernández-Kranz, Daniel & Lacuesta, Aitor & Rodríguez-Planas, Núria, 2010. "Chutes and Ladders: Dual Tracks and the Motherhood Dip," IZA Discussion Papers 5403, Institute of Labor Economics (IZA).

    More about this item

    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:plo:pone00:0286680. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.