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Hypothesis testing for detecting outlier evaluators

Author

Listed:
  • Xu Li

    (Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA)

  • Zucker David M.

    (Department of Statistics and Data Science, Hebrew University of Jerusalem, Mt. Scopus, Jerusalem, Israel)

  • Wang Molin

    (Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA)

Abstract

In epidemiological studies, the measurements of disease outcomes are carried out by different evaluators. In this paper, we propose a two-stage procedure for detecting outlier evaluators. In the first stage, a regression model is fitted to obtain the evaluators’ effects. Outlier evaluators have different effects than normal evaluators. In the second stage, stepwise hypothesis tests are performed to detect outlier evaluators. The true positive rate and true negative rate of the proposed procedure are assessed in a simulation study. We apply the proposed method to detect potential outlier audiologists among the audiologists who measured hearing threshold levels of the participants in the Audiology Assessment Arm of the Conservation of Hearing Study, which is an epidemiological study for examining risk factors of hearing loss.

Suggested Citation

  • Xu Li & Zucker David M. & Wang Molin, 2024. "Hypothesis testing for detecting outlier evaluators," The International Journal of Biostatistics, De Gruyter, vol. 20(2), pages 419-431.
    • Handle: RePEc:bpj:ijbist:v:20:y:2024:i:2:p:419-431:n:1006
    DOI: 10.1515/ijb-2023-0004
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