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Table 3 Negative Binomial Model estimation of PIN crash risk among taxi drivers

From: Predicting personal injury crash risk through working conditions, job strain, and risky driving behaviors among taxi drivers

Variables	Model I				Model II
Variables	Coef	SE	z value	p	Coef	SE	z value	p
Intercept	−7.082	0.901	−7.857	< 0.001	−6.850	0.364	−18.80	< 0.001
GEND	−0.101	0.250	−0.406	0.684
AGE	0.004	0.011	0.423	0.671
EDU	−0.043	0.088	− 0.492	0.625
HOUR	0.004	0.059	0.064	0.956
DRES	0.164	0.111	1.473	0.142
FEE	0.055	0.109	0.506	0.606
REDL	0.450	0.068	7.319	< 0.001	0.521	0.065	8.054	< 0.001
SPEE	0.242	0.093	2.596	0.001	0.241	0.074	3.253	0.001
ANNO	0.153	0.085	1.791	0.024	0.154	0.068	2.260	0.024
AGGR	0.278	0.069	4.037	< 0.001	0.276	0.069	3.981	< 0.001
FATI	0.331	0.061	5.468	< 0.001	0.313	0.057	5.524	< 0.001
PHON	0.230	0.083	2.757	< 0.001	0.220	0.057	3.905	< 0.001
OVTA	0.222	0.084	2.651	< 0.001	0.245	0.055	4.467	< 0.001
PARK	0.025	0.231	0.107	0.915
Log likelihood	− 366.1				− 368.5
AIC	764.1				755.0

SE Std. Err

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