Diagnostic methods in the context of the Highway Safety Manual (HSM) aim to identify abnormalities or patterns in crash occurrence which may provide an important clue to an effective remedy. These methods are used to assess the nature of the safety problem and on its basis select a countermeasure for which there is a known crash modification factor. Two approaches are presently used to perform diagnostic examinations: the test of proportions and crash type-specific safety performance functions (SPFs). The test of proportions uses empirical proportions (diagnostic norms) of crash types and crash attributes within congestion strata, the total number of crashes, and the number of observed crashes of a specific type to compute the cumulative probability of the observed outcome. Crash type-specific SPFs are used to identify sites at which the observed frequency or severity of specific crash types is higher than expected. This paper examines the strengths of both methods by applying them to the same datasets and comparing the results. The findings suggest that the test of proportions works well in identifying locations with a single disproportionally frequent crash type. Crash type-specific SPFs can identify locations having multiple crash types with an elevated frequency, but will not identify locations having crash patterns susceptible to correction but not having elevated counts. Findings also suggest that the degree of stratification in diagnostic norms influences the number of overlapping sites detected by both methods.
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