title: Possible aggregation biases in road safety research and a mechanism approach to accident modeling.
abstract: In accident reconstruction, individual road accidents are treated as essentially deterministic events, although incomplete information can leave one uncertain about how exactly an accident happened. In statistical studies, on the other hand, accidents are treated as individually random, although the parameters governing their probability distributions may be modeled deterministically. Here, a simple deterministic model of a vehicle/pedestrian encounter is used to illustrate how naïvely applying statistical methods to aggregated data could lead to an ecological fallacy and to Simpson's paradox. It is suggested that these problems occur because the statistical regularities observed in accident data have no independent status, but are simply the result of aggregating particular types and frequencies of mechanisms.
authors.affiliation: Department of Civil Engineering, University of Minnesota, 122 CivE, 500 Pillsbury Drive SE, Minneapolis, MN 55455, USA. drtrips@imn.edu
authors.forename: Gary A
authors.initials: GA
authors.lastname: Davis
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data*; D015982:Bias; D015984:Causality; D003627:Data Interpretation, Statistical; D006801:Humans; D008962:Models, Theoretical