Pitfalls of Statistical Methods in Traffic Psychology

Pitfalls of Statistical Methods in Traffic Psychology

de Winter, J.C.F. (TU Delft Human-Robot Interaction)
Dodou, D. (TU Delft Medical Instruments & Bio-Inspired Technology)

Vickerman, Roger (editor)

2021

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.

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

http://resolver.tudelft.nl/uuid:7ac19e31-49a3-4f87-b8b2-54f066b05e17

https://doi.org/10.1016/B978-0-08-102671-7.10665-7

Elsevier

2021-11-17

978-0-08-102672-4

International Encyclopedia of Transportation, 7

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

book chapter

© 2021 J.C.F. de Winter, D. Dodou