Table 2.

Spatial Lag and Error Models Predicting STI Rates

	Without Network	Spatial Network		Commuting Network		Public Transit Network
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7
Disadvantage	−0.060* (0.029)	−0.064** (0.022)		−0.038 (0.031)		−0.054 (0.030)
Stability	−0.000 (0.019)	−0.004 (0.013)	−0.004 (0.013)	−0.020 (0.023)	−0.019 (0.023)	−0.021 (0.023)	−0.023 (0.023)
Diversity	−0.047* (0.018)	−0.037* (0.016)	−0.013 (0.014)	−0.039 (0.021)	−0.029 (0.020)	−0.053** (0.019)	−0.037* (0.017)
Local Workers	0.008 (0.021)	0.002 (0.018)	0.005 (0.018)	−0.007 (0.018)	−0.008 (0.018)	−0.001 (0.021)	−0.002 (0.021)
Prior STI Rate	0.390*** (0.030)	0.296*** (0.031)	0.289*** (0.032)	0.380*** (0.032)	0.373*** (0.032)	0.385*** (0.033)	0.375*** (0.032)
Network STI Risk		0.603*** (0.064)	0.589*** (0.070)	0.960*** (0.011)	0.960*** (0.011)	0.883*** (0.006)	0.883*** (0.006)
Error Variance Parameter		−0.629*** (0.108)	−0.588*** (0.116)	0.961*** (0.010)	0.962*** (0.010)	0.883*** (0.006)	0.883*** (0.006)
Time Fixed Effects	Yes	Yes	Yes	Yes	Yes	Yes	Yes
AIC	−894.57	−921.79	−915.45	−1268.55	−1269.08	−3391.84	−3390.63
BIC	−806.21	−823.62	−822.18	−1170.38	−1175.81	−3293.66	−3297.36
Neighborhoods=77; Observations=1,001

Note: Standard errors in parentheses. All models include year dummies. The Wald test of spatial autocorrelation is significant across all models at p<0.001.

^*p<0.05,

^**p<0.01,

^***p<0.001