Hypothesis testing for detecting outlier evaluators.

Li Xu, David M Zucker, Molin Wang
Author Information
  1. Li Xu: Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. ORCID
  2. David M Zucker: Department of Statistics and Data Science, Hebrew University of Jerusalem, Mt. Scopus, Jerusalem, Israel.
  3. Molin Wang: 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.

Keywords

References

  1. Biometrics. 1986 Mar;42(1):121-30 [PMID: 3719049]
  2. Am J Epidemiol. 2020 Mar 2;189(3):204-214 [PMID: 31608356]
  3. J Prosthet Dent. 2015 Aug;114(2):217-22 [PMID: 25976708]
  4. BMC Med Res Methodol. 2023 Aug 1;23(1):177 [PMID: 37528402]
  5. Am J Public Health. 2016 Sep;106(9):1573-81 [PMID: 27459450]
  6. Bioinformatics. 2022 Aug 10;38(16):4011-4018 [PMID: 35762974]
  7. BMC Med Res Methodol. 2018 Nov 19;18(1):141 [PMID: 30453897]
  8. J Am Geriatr Soc. 2021 Nov;69(11):3103-3113 [PMID: 34028002]

MeSH Term

Humans
Hearing Loss
Models, Statistical
Computer Simulation
Regression Analysis
Data Interpretation, Statistical
Auditory Threshold

Word Cloud

Created with Highcharts 10.0.0evaluatorsoutlierepidemiologicaldifferentproceduredetectingstageeffectsdetecttruerateproposedstudyaudiologistshearingstudiesmeasurementsdiseaseoutcomescarriedpaperproposetwo-stagefirstregressionmodelfittedobtainevaluators'OutliernormalsecondstepwisehypothesistestsperformedpositivenegativeassessedsimulationapplymethodpotentialamongmeasuredthresholdlevelsparticipantsAudiologyAssessmentArmConservationHearingStudyexaminingriskfactorslossHypothesistestingaudiometricdataevaluatoroutliersdetectionqualitycontrol

Similar Articles

Cited By

No available data.