A probabilistic model for identifying errors in data editing

Joseph I. Naus, Thomas G. Johnson, Ramiro Montalvo

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Certain data screening systems incorporate large numbers of logical checks on data entering the system. When violated, these logical checks indicate that various combinations of variates are in error. This article provides a model for assigning a probability measure to identify variates in error when there is a simultaneous violation of a set of logical checks. For certain symmetry conditions, the measure is a reasonable approximation to the posterior probability that given a violation of a set of conditions, a variate is in error.

Original languageEnglish (US)
Pages (from-to)943-950
Number of pages8
JournalJournal of the American Statistical Association
Volume67
Issue number340
DOIs
StatePublished - Dec 1972

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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