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Systematically misclassified binary dependent variables

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  • Vidhura Tennekoon
  • Robert Rosenman

Abstract

When a binary dependent variable is misclassified, that is, recorded in the category other than where it really belongs, probit and logit estimates are biased and inconsistent. In some cases, the probability of misclassification may vary systematically with covariates, and thus be endogenous. In this paper, we develop an estimation approach that corrects for endogenous misclassification, validate our approach using a simulation study, and apply it to the analysis of a treatment program designed to improve family dynamics. Our results show that endogenous misclassification could lead to potentially incorrect conclusions unless corrected using an appropriate technique.

Suggested Citation

  • Vidhura Tennekoon & Robert Rosenman, 2016. "Systematically misclassified binary dependent variables," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(9), pages 2538-2555, May.
  • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:9:p:2538-2555
    DOI: 10.1080/03610926.2014.887105
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    Cited by:

    1. Matthew Birch & Robert Rosenman, 2019. "How Much Does Merit Aid Actually Matter? Revisiting Merit Aid and College Enrollment When Some Students “Come Anyway”," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(6), pages 760-802, September.
    2. Vidhura Tennekoon & Robert Rosenman, 2013. "Bias in Measuring Smoking Behavior," Working Papers 2013-10, School of Economic Sciences, Washington State University.
    3. Darren J. Mayne & Geoffrey G. Morgan & Bin B. Jalaludin & Adrian E. Bauman, 2019. "Area-Level Walkability and the Geographic Distribution of High Body Mass in Sydney, Australia: A Spatial Analysis Using the 45 and Up Study," IJERPH, MDPI, vol. 16(4), pages 1-29, February.
    4. Tennekoon, Vidhura S., 2016. "The equivalence of three latent class models and ML estimators," Economics Letters, Elsevier, vol. 141(C), pages 147-150.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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