Pitfalls of Statistical Methods in Traffic Psychology

Research output: Chapter in Book/Conference proceedings/Edited volumeEntry for encyclopedia/dictionaryScientificpeer-review

Abstract

This article highlights four common pitfalls in the use of statistics in the area of traffic psychology. Through computer simulations of scenarios that are typical in the field, it is first shown that a statistically significant P-value does not prove that the effect is true, especially when the effect is surprising and the P-value barely significant. Second, we show that “everything is correlated”, a phenomenon which has important ramifications for significance testing. Third, we explain the perils of two-stage testing and data peeking. Finally, we explain that the violation of independence can easily lead to false positives.
Original languageEnglish
Title of host publicationInternational Encyclopedia of Transportation
EditorsRoger Vickerman
PublisherElsevier
Pages87-95
ISBN (Print)978-0-08-102672-4
DOIs
Publication statusPublished - 2021

Keywords

  • Bias
  • Common method variance
  • Correlation coefficient
  • False positives
  • Hypothesis testing
  • Outliers
  • Power
  • Questionable research practices
  • Response style
  • Sample size
  • Statistical significance
  • t-test
  • Test assumptions
  • Type I errors

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