Accounting for Attribute Non-Attendance and Common-Metric Aggregation in the Choice of Seat Belt Use, a Latent Class Model with Preference Heterogeneity

A choice to use a seat belt is largely dependent on the psychology of vehicles’ occupants, and thus those decisions are expected be characterized by preference heterogeneity. Despite importance safety roadways, majority existing studies ignored heterogeneity in data used very standard statistical or descriptive method identify factors using seatbelt. Application right crucial unlock underlying being made occupants. Thus, this study was conducted contributory front-seat passengers’ usage, while accounting for The latent class model has been offered replace mixed logit replacing continuous distribution with discrete one. However, one shortcomings that homogeneity assumed across same class. further extension relax assumption allowing some parameters vary group. could still extended overlay attributes considering non-attendance (ANA), aggregation common-metric (ACMA). make comparison goodness fit discussed models. Beside based fit, share individuals each see how it changes various specifications. In summary, results indicated adding another layer account within (LC) model, ANA ACMA would improve fit. It content manuscript ANA, an extra does not just but impacts allocation