Hypothesis testing for detecting outlier evaluators

Li Xu, David M. Zucker, Molin Wang

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)419-431
Number of pages13
JournalInternational Journal of Biostatistics
Volume20
Issue number2
DOIs
StatePublished - 1 Nov 2024

Keywords

  • audiometric data
  • evaluator outliers
  • outlier detection
  • quality control

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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