This document discusses the importance of controlling for self-reported exposure in traffic accident prediction studies. It notes that accident risk increases with increased driving exposure. However, most studies do not control for exposure beyond calendar time. Self-reported exposure data is unreliable and can create spurious associations. The study analyzed data from over 24,000 drivers, controlling for self-reported mileage. It found a 20-30% reduction in the explained variance of crashes and offenses when controlling for mileage. The conclusion is that exposure has a strong effect on crash prediction but is often not properly controlled for, leading to overestimation of the effects of other variables.

1. Controlling for self-reported exposure in
traffic accident prediction studies
Anders af Wåhlberg
Department of Psychology
Uppsala university

2. Exposure to risk of traffic accident
• As drivers drive, they expose themselves, and
accident risk increases

3. Exposure to risk of traffic accident
• As drivers drive, they expose themselves, and
accident risk increases
• When differences in accident record is
predicted, what is it we predict?

4. Exposure to risk of traffic accident
• As drivers drive, they expose themselves, and
accident risk increases
• When differences in accident record is
predicted, what is it we predict?
• Accident proneness, exposure proneness, or
both?

5. Exposure to risk of traffic accident
• As drivers drive, they expose themselves, and
accident risk increases
• When differences in accident record is
predicted, what is it we predict?
• Accident proneness, exposure proneness, or
both?
• Most studies on accident record do not
control for exposure beyond calender time

6. Exposure to risk of traffic accident
• Is exposure a mediator or a confounder?

7. Exposure to risk of traffic accident
• Is exposure a mediator or a confounder?
• If exposure does not correlate with the
predictor, it is a confounder

8. Exposure to risk of traffic accident
• Is exposure a mediator or a confounder?
• If exposure does not correlate with the
predictor, it is a confounder
• What psychological variables correlate with
exposure?

9. Exposure to risk of traffic accident
• Is exposure a mediator or a confounder?
• If exposure does not correlate with the
predictor, it is a confounder
• What psychological variables correlate with
exposure?
• What is the difference if we control for
exposure?

10. Self-reported exposure to risk of
traffic accident

11. Self-reported exposure to risk of
traffic accident
• Is self-reported mileage a mediator or a
confounder?

12. Self-reported exposure to risk of
traffic accident
• Is self-reported mileage a mediator or a
confounder?
• Self-reported mileage is unreliable

13. Self-reported exposure to risk of
traffic accident
• Is self-reported mileage a mediator or a
confounder?
• Self-reported mileage is unreliable
• Self-report bias can create associations with
other variables

14. Study: Controlling for self-reported mileage
Method

15. Study: Controlling for self-reported mileage
Method
• Samples: 4 (total N=24 016)

16. Study: Controlling for self-reported mileage
Method
• Samples: 4 (total N=24 016)
• Self-reported crashes and offences

17. Study: Controlling for self-reported mileage
Method
• Samples: 4 (total N=24 016)
• Self-reported crashes and offences
• Questionnaires scales: DAS, DBI, SSS, drugs,
DBQ-V, DIM

18. Study: Controlling for self-reported mileage
Method
• Samples: 4 (total N=24 016)
• Self-reported crashes and offences
• Questionnaires scales: DAS, DBI, SSS, drugs,
DBQ-V, DIM
• Analysis: Comparing zero-order and partial
correlations between crashes/offences and
scales, controlling for mileage

19. Study: Controlling for self-reported mileage
Results

20. Study: Controlling for self-reported mileage
Results
• 20% reduction in explained variance for
crashes

21. Study: Controlling for self-reported mileage
Results
• 20% reduction in explained variance for
crashes
• 30% reduction in explained variance for
offences

22. Conclusions

23. Conclusions
• There is a strong effect of exposure on crash
prediction in self-reported data

24. Conclusions
• There is a strong effect of exposure on crash
prediction in self-reported data
• Most studies on accident prediction use self-
reported data

25. Conclusions
• There is a strong effect of exposure on crash
prediction in self-reported data
• Most studies on accident prediction use self-
reported data
• Few accident prediction studies control for
exposure beyond calender time

26. Conclusions
• There is a strong effect of exposure on crash
prediction in self-reported data
• Most studies on accident prediction use self-
reported data
• Few accident prediction studies control for
exposure beyond calender time
• Therefore; effect sizes have been over-
estimated for many variables

27. Thank you for your attention
Anders af Wåhlberg
Department of Psychology
Uppsala university