Abstract
Cross-sectional and panel (or longitudinal) studies are two types of observational studies that assess exposure and the outcome at one point or a short period of time in a sample population. These studies cannot be used to infer causality because data do not include information on confounding factors and other variables that affect the relationship between the existed cause and effect. In highway safety research, it is unethical and uneconomical to conduct an experiment in a real traffic environment, and thus cross-sectional studies are commonly preferred. Before developing cross-sectional models, data and modeling issues, and various data cleaning approaches should be considered. During the model development stage, efforts must be placed on variable selection, functional forms, crash variance, sample size determination, and outlier analysis. As developing a new model is a time-consuming effort, emphasis should be laid on transferability of existing models from one jurisdiction to another.
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