A Data‐Based Method for Bivariate Outlier Detection: Application to Automatic Blood Pressure Recording Devices

L. A. Clark, L. Denby, D. Pregibon, G. A. Harshfield, T. G. Pickering, S. Blank, J. H. Laragh

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

The rapidly increasing use of automatic devices for the measurement of blood pressure has made it increasingly important to identify artifactual readings. This paper describes an objective technique for isolating a small but adjustable percentage of the readings that are likely artifacts. The validity of these readings requires the subjective judgment of the clinician. The proposed methodology substantially reduces the number of readings to be manually examined by not only taking into account the level of systolic and diastolic blood pressure per se, but also the relationship between the two and how they vary according to differential covariate information. The method can be applied to homogeneous populations, or as illustrated in this paper, to heterogeneous populations after adjustment for known or suspected sources of variability. Thus the technique is applicable to protocols which examine blood pressure, or for that matter any two (or more) related variables, during a variety of experimental procedures including psychophysiological reactivity tasks.

Original languageEnglish (US)
Pages (from-to)119-125
Number of pages7
JournalPsychophysiology
Volume24
Issue number1
DOIs
StatePublished - Jan 1 1987
Externally publishedYes

Keywords

  • Analysis of covariance
  • Artifacual readings
  • Blood pressure monitoring
  • Residual analysis

ASJC Scopus subject areas

  • Neuroscience(all)
  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Endocrine and Autonomic Systems
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Biological Psychiatry

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  • Cite this

    Clark, L. A., Denby, L., Pregibon, D., Harshfield, G. A., Pickering, T. G., Blank, S., & Laragh, J. H. (1987). A Data‐Based Method for Bivariate Outlier Detection: Application to Automatic Blood Pressure Recording Devices. Psychophysiology, 24(1), 119-125. https://doi.org/10.1111/j.1469-8986.1987.tb01872.x