TABLE 3—
Estimates of Effects for 5 Types of Crashes on Road Segments and at Intersections: New York City, 1996–2006
| Total Crashes | Vehicle Crashes | Pedestrian Crashes | Bicycle Crashes | Injurious or Fatal Crashes | |
| Crashes on segments | |||||
| Dispersion parametera | 1.385* (0.079) | 1.601* (0.104) | 1.543* (0.197) | 1.398* (0.095) | |
| Treatment group, T1b (a) | −0.464* (0.083) | −0.484* (0.107) | −0.500* (0.205) | 0.011 (0.263) | −0.475* (0.096) |
| Comparison group, T1c (b) | −0.407* (0.064) | −0.426* (0.081) | −0.343* (0.119) | −0.401* (0.235) | −0.420* (0.071) |
| a − b, estimate (SE; 95% CI) | −0.057 (0.106; −0.265, 0.150) | −0.058 (0.134; −0.321, 0.205) | −0.157 (0.236; −0.619, 0.369) | 0.412 (0.352; −0.279, 1.102) | −0.056 (0.120; −0.290, 0.178) |
| % change in crashes, estimate (SE; 95% CI) | −5.6 (10.1; −25.4, 14.2) | −5.6 (12.8; −30.7, 19.5) | −14.5 (21.0; −55.7, 26.8) | 50.9 (58.3; −63.4, 165.2) | −5.4 (11.4; −27.8, 17.0) |
| Crashes at intersections | |||||
| Dispersion parametera | 0.986* (0.030) | 1.080* (0.035) | 0.975* (0.057) | 1.010* (0.033) | |
| Treatment group, T1b (a) | −0.209* (0.040) | −0.339* (0.047) | 0.090 (0.072) | 0.201 (0.107) | −0.218* (0.044) |
| Comparison group, T1c (b) | −0.264* (0.030) | −0.346* (0.034) | 0.027 (0.050) | −0.047 (0.083) | −0.286* (0.032) |
| a − b, estimate (SE; 95% CI) | 0.055 (0.050; −0.042, 0.153) | 0.007 (0.058; −0.105, 0.120) | 0.063 (0.088; −0.108, 0.235) | 0.248 (0.135; −0.016, 0.514) | 0.068 (0.055; −0.039, 0.175) |
| % change in crashes, estimate (SE; 95% CI) | 5.7 (5.3; −4.7, 16.1) | 0.7 (5.9; −10.7, 12.2) | 6.5 (9.4; −12.0, 20.0) | 28.1 (17.5; −6.3, 62.4) | 7.0 (5.9; −4.5, 18.5) |
Note. The treatment group consisted of roadway segments in New York City where bicycle lanes had been installed from 1996 through 2006. The comparison group comprised locations without bicycle lanes but with segment- or intersection-level characteristics comparable to those of the treatment group.
Dispersion parameter is not applicable for bicycle crashes because bicycle crashes data were not overdispersed, and thus they were modeled by Poisson regression instead of negative binomial.
Dummy variable: 1 if the data point comes from the treatment group in the after period and 0 otherwise; a is the coefficient of this dummy variable
Dummy variable: 1 if the data point comes from the comparison group in the after period and 0 otherwise; b is the coefficient of this dummy variable
*P < .05.