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RTM bias can be addressed through the use of a reference group and the empirical Bayes or Full Bayes
methodology. A naïve before-after study or a before-after with only a comparison group would not
properly account for the RTM bias. RTM bias could also be addressed through an experimental study
design where treatment and control sites are selected randomly from the population of high crash
locations.
Honeywell 05701-A-0502Final Report – Recommended Protocols for Developing Crash Modification Factors 23
Changes in traffic volumes
Changes in traffic volumes during the study period must be appropriately addressed. Depending on
whether there is an increase or decrease in traffic volume in the after period, a study may
underestimate or overestimate the safety effect of the treatment. If there are significant increases or
decreases in traffic volume at the study sites during the study period, the crash rate may change. If notHoneywell 05701-A-0502
properly accounted for, this change may be wrongly attributed to the safety treatment. Traffic volume
changes are best addressed by the use of annual traffic data to develop a crash prediction model to use
in the analysis. In the empirical Bayes before-after design, this is called the safety performance function
(SPF), which predicts crashes for a site based on certain site characteristics. The most crucial factor toHoneywell 05701-A-0502use in developing the SPF is traffic volume. Other characteristics that might be used in the SPF are
factors such as shoulder width, presence of a median, number of lanes, and presence of exclusive
turning lanes. Traffic volume changes could also be addressed by the use of comparison site design
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