Table 3.
Parameter estimates for the natural log of the ratio of drinking to non-drinking drivers younger than age 21 in fatal crashes. In this model, “region” and data from the 14 States that had the possession/purchase laws in place in 1982 serve as a covariate. (R2 = 0.49).
| Parameter | B | SE (B) | Effect Size* (%) | P-Value | 95% CI for B | Variance explained (partial Eta2) | |
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Possession & Purchasing Laws | −0.12 | 0.06 | −11.2% | 0.041 | −0.23 | 0.00 | 0.01 |
| .08 Law | −0.80 | 0.24 | −55.1% | 0.001 | −1.27 | −0.33 | 0.03 |
| ALR Law | −0.26 | 0.05 | −22.6% | <0.001 | −0.35 | −0.17 | 0.09 |
| Under 21 ratio in comparison1 States (in log Transformed metric) | 0.46 | 0.11 | <0.001 | 0.24 | 0.68 | 0.05 | |
| % Urbanization | −0.32 | 0.15 | 0.038 | −0.62 | −0.02 | 0.01 | |
| Unemployment | 0.03 | 0.01 | 0.022 | 0.00 | 0.05 | 0.02 | |
| VMT per licensed driver | 0.03 | 0.02 | 0.048 | 0.00 | 0.06 | 0.01 | |
| Categorical Factors | F- statistic | df | P- Value | partial Eta2 | |||
| Region (Region 10 = Ref cat) | 16.68 | 9 | <0.001 | 0.32 | |||
*
Effect size is the percentage change in the outcome variable’s metric, per unit change in the predictor variable. For binary variables representing presence/absence of a law, it can be interpreted as the proportional amount of change in the outcome associated with the presence of a law.