Research Article
Insights on Crash Injury Severity Control from Novice and Experienced Drivers: A Bivariate Random-Effects Probit Analysis
Table 1
Results for bivariate probit and bivariate random-effects probit models.
| Variable | Bivariate probit | Bivariate random-effects probit | Coef. | Std. Err. | z | > |z| | Coef. | Std. Err. | z | > |z| |
| Novice driver injury model | | | | | | | | | Crash type | −0.109 | 0.020 | −5.49 | 0.000 | −0.110 | 0.019 | −5.01 | 0.000 | Vehicle 2 type | −0.050 | 0.022 | −2.25 | 0.024 | −0.049 | 0.024 | −2.22 | 0.012 | Pedestrian | 1.329 | 0.365 | 3.63 | 0.000 | 1.394 | 0.384 | 3.61 | 0.000 | Motorcyclist | 1.513 | 0.436 | 3.46 | 0.001 | 1.671 | 0.490 | 3.44 | 0.001 | Constant | 0.887 | 0.079 | 11.15 | 0.000 | 0.882 | 0.080 | 11.17 | 0.000 | Experienced driver injury model | | | | | | | | | Crash type | −0.055 | 0.021 | −2.61 | 0.009 | −0.056 | 0.020 | −2.61 | 0.005 | Vehicle 2 driver condition | 0.056 | 0.016 | 3.52 | 0.000 | 0.057 | 0.016 | 3.57 | 0.000 | First harm | −0.106 | 0.013 | −7.81 | 0.000 | −0.106 | 0.014 | −7.84 | 0.000 | Highway factor | −0.616 | 0.182 | −3.37 | 0.001 | −0.629 | 0.174 | −3.38 | 0.001 | Constant | 1.668 | 0.195 | 8.52 | 0.000 | 1.681 | 0.191 | 8.51 | 0.000 | α1 | 1.052 | 0.189 | 6.82 | 0.000 | 1.112 | 0.155 | 7.18 | 0.000 | α2 | 0.908 | 0.263 | 3.65 | 0.000 | 0.948 | 0.220 | 4.31 | 0.000 | ρα | −0.256 | 0.087 | | | −0.287 | 0.085 | | | ρɛ | | | | | 0.416 | 0.086 | | | Goodness of fit | | | | | | | | | No. of observations | 1999 | 1999 | Log-likelihood at convergence | −925.747 | −978.069 | Log-likelihood at zero | −1809.635 | −1894.337 |
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Note. Coef. = coefficient; Std. Err. = standard error; ∗significant at the 5% level.
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