Table 3.

Multivariable generalized ordered logistic regression model.

Multivariable Generalized Ordered Logistic Regression (n = 2165)	Low versus Medium and High (Equation (1))			Low and Medium versus High (Equation (2))			* Gamma (Deviations from Proportionality)
	OR	p-Value	95% CI	OR	p-Value	95% CI	OR	p-Value
Breed Group (baseline is non-sporting)
Herding	0.89	0.456	0.65–1.21
Hound	0.68	0.184	0.38–1.20
Sporting	0.69	0.032	0.49–0.97
Terrier	0.71	0.041	0.51–0.99	1.10	0.630	0.75–1.61	1.55	0.003
Toy	0.79	0.277	0.52–1.20
Working	0.94	0.689	0.68–1.29
Incident location (baseline is public space)
In home	8.17	<0.001	6.08–10.98
Off-leash park	3.20	<0.001	2.18–4.68
Owner’s property	2.38	<0.001	1.91–2.97
Dog Sex (baseline is intact female)
Intact male	1.50	0.01	1.09–2.06
Neutered male	1.77	<0.001	1.31–2.40	1.02	0.921	0.71–1.46	0.57	<0.001
Spayed female	0.93	0.67	0.67–1.29
Victim age (baseline is adult)
Child	1.39	0.004	1.11–1.73
Youth	1.55	0.020	1.07–2.25
Older adult	1.74	<0.001	1.33–2.27
Dog age (baseline is 0–2)
3–6	1.26	0.026	1.03–1.54
7+	1.46	0.002	1.16–1.86
Year (baseline is 2017)
2012	1.42	0.034	1.03–1.97
2013	1.20	0.253	0.88–1.65
2014	1.09	0.579	0.81–1.46
2015	0.95	0.750	0.71–1.28
2016	0.90	0.473	0.67–1.21
Constant	0.40	<0.001	0.25–0.62	0.06	<0.001	0.04–0.10

* Gammas represents the difference in coefficients (logit scale) from Equation (2) − Equation (1). For example: For the terrier breed group Equation (1): log (0.71) = −0.34, Equation (2): log (1.10) = 0.09, Gamma: log (1.55) = 0.438. To calculate Gamma: = 0.09 − (−0.34) = 0.435.