Evaluation and Comparison of Roadside Crash Injury Metrics (2023)

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285 Appendix D: Chapter 6 Supplemental Material D.1 Side Crash Initial Models Table D-1. Parameters for the MDV initial side logistic regression model used to predict occupant MAIS2+F injuries. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -3.664 1.548 0.021** Lateral Delta-v β1, Delta-v (m/s) 0.358 0.154 0.023** Belt Status β2, Belted -2.394 0.899 0.010** Impact Type β3, Nearside 1.623 0.603 0.009** Age β4, Age ≥ 65 1.133 0.657 0.090 Sex β5, Male 0.595 0.968 0.541 Obesity β6, BMI ≥ 30 kg/m2 1.106 0.678 0.108 Seating Location β7, Driver -0.469 1.115 0.676 Vehicle Type β8, Passenger Car 0.044 1.178 0.970 Table D-2. Parameters for the OIV initial side logistic regression model used to predict occupant MAIS2+F injuries. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -3.559 1.576 0.028** Lateral OIV β1, OIV (m/s) 0.354 0.153 0.025** Belt Status β2, Belted -2.377 0.891 0.010** Impact Type β3, Nearside 1.567 0.598 0.011** Age β4, Age ≥ 65 1.116 0.654 0.094 Sex β5, Male 0.628 0.961 0.516 Obesity β6, BMI ≥ 30 kg/m2 1.119 0.682 0.107 Seating Location β7, Driver -0.531 1.135 0.642 Vehicle Type β8, Passenger Car 0.063 1.178 0.957 Table D-3. Parameters for the OLC initial side logistic regression model used to predict occupant MAIS2+F injuries. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -2.664 1.495 0.080 Lateral OLC β1, OLC (g) 0.155 0.055 0.007** Belt Status β2, Belted -2.280 0.880 0.012** Impact Type β3, Nearside 1.876 0.615 0.003** Age β4, Age ≥ 65 1.128 0.618 0.073 Sex β5, Male 0.295 0.957 0.759 Obesity β6, BMI ≥ 30 kg/m2 1.040 0.710 0.148 Seating Location β7, Driver -0.380 1.073 0.725 Vehicle Type β8, Passenger Car -0.093 1.138 0.935 Table D-4. Parameters for the ASI initial side logistic regression model used to predict occupant MAIS2+F injuries. ** indicates statistical significance (p-value < 0.05).

286 Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -3.774 1.595 0.021** Lateral ASI β1, ASI 1.895 0.681 0.007** Belt Status β2, Belted -2.240 0.908 0.017** Impact Type β3, Nearside 1.841 0.682 0.009** Age β4, Age ≥ 65 1.243 0.629 0.053 Sex β5, Male 0.465 0.967 0.633 Obesity β6, BMI ≥ 30 kg/m2 0.965 0.704 0.176 Seating Location β7, Driver -0.393 1.095 0.721 Vehicle Type β8, Passenger Car -0.059 1.169 0.960 Table D-5. Parameters for the VPI initial side logistic regression model used to predict occupant MAIS2+F injuries. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -3.932 1.617 0.018** Lateral VPI β1, VPI (m/s2) 0.009 0.004 0.011** Belt Status β2, Belted -2.220 0.879 0.014** Impact Type β3, Nearside 1.834 0.652 0.007** Age β4, Age ≥ 65 1.160 0.622 0.067 Sex β5, Male 0.460 0.975 0.639 Obesity β6, BMI ≥ 30 kg/m2 0.981 0.701 0.167 Seating Location β7, Driver -0.355 1.092 0.746 Vehicle Type β8, Passenger Car -0.056 1.176 0.962 D.2 Side Crash Region-Specific Initial Models Head and Face Table D-6. Parameters for the MDV logistic regression model used to predict occupant MAIS2+F injuries in side crashes. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -7.194 1.739 < 0.001** Lateral Delta-v β1, Delta-v (m/s) 0.962 0.260 < 0.001** Belt Status β2, Belted -6.697 1.580 < 0.001** Impact Type β3, Nearside 3.504 1.745 0.049** Age β4, Age ≥ 65 1.286 1.167 0.275 Sex β5, Male -2.574 1.845 0.168 Obesity β6, BMI ≥ 30 kg/m2 0.714 0.920 0.441 Table D-7. Parameters for the OIV logistic regression model used to predict occupant MAIS2+F injuries in side crashes. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -7.054 1.716 < 0.001** Lateral OIV β1, Delta-v (m/s) 0.957 0.258 < 0.001** Belt Status β2, Belted -6.623 1.532 < 0.001** Impact Type β3, Nearside 3.322 1.697 0.055 Age β4, Age ≥ 65 1.330 1.142 0.249 Sex β5, Male -2.474 1.812 0.177 Obesity β6, BMI ≥ 30 kg/m2 0.731 0.914 0.427 Table D-8. Parameters for the OLC logistic regression model used to predict occupant MAIS2+F injuries in side crashes. ** indicates statistical significance (p-value < 0.05).

287 Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -3.993 1.020 < 0.001** Lateral OLC β1, Delta-v (m/s) 0.325 0.065 < 0.001** Belt Status β2, Belted -5.779 0.980 < 0.001** Impact Type β3, Nearside 3.486 1.057 0.002** Age β4, Age ≥ 65 1.306 0.998 0.196 Sex β5, Male -2.581 1.329 0.057 Obesity β6, BMI ≥ 30 kg/m2 0.827 0.872 0.347 Table D-9. Parameters for the ASI logistic regression model used to predict occupant MAIS2+F injuries in side crashes. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -7.164 1.669 < 0.001** Lateral ASI β1, Delta-v (m/s) 4.661 1.136 < 0.001** Belt Status β2, Belted -6.477 1.522 < 0.001** Impact Type β3, Nearside 4.201 1.812 0.024** Age β4, Age ≥ 65 1.089 1.192 0.365 Sex β5, Male -2.998 1.927 0.125 Obesity β6, BMI ≥ 30 kg/m2 0.681 1.033 0.512 Table D-10. Parameters for the VPI logistic regression model used to predict occupant MAIS2+F injuries in side crashes. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient Std. Error p-Value --- β0, Intercept -8.577 2.228 < 0.001** Lateral VPI β1, Delta-v (m/s) 0.026 0.007 0.001** Belt Status β2, Belted -6.788 1.741 < 0.001** Impact Type β3, Nearside 4.974 2.266 0.032** Age β4, Age ≥ 65 0.863 1.175 0.465 Sex β5, Male -3.314 1.905 0.087 Obesity β6, BMI ≥ 30 kg/m2 0.565 0.979 0.566