Power computations in time series analyses for traffic safety interventions.
The evaluation of traffic safety interventions or other policies that can affect road safety often requires the collection of administrative time series data, such as monthly motor vehicle collision data that may be difficult and/or expensive to collect. Furthermore, since policy decisions may be based on the results found from the intervention analysis of the policy, it is important to ensure that the statistical tests have enough power, that is, that we have collected enough time series data both before and after the intervention so that a meaningful change in the series will likely be detected. In this short paper, we present a simple methodology for doing this. It is expected that the methodology presented will be useful for sample size determination in a wide variety of traffic safety intervention analysis applications. Our method is illustrated with a proposed traffic safety study that was funded by NIH.
McLeod
A Ian
AI
Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario, Canada N6A 5B7. aimcleod@uwo.ca
Vingilis
E R
ER
D000056:Accident Prevention / Q000706:statistics & numerical data; D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data; D001336:Automobiles / Q000706:statistics & numerical data*; D003625:Data Collection; D006801:Humans; D015233:Models, Statistical; D012449:Safety / Q000706:statistics & numerical data*; D018401:Sample Size; D013997:Time Factors; D013996:Time and Motion Studies