Table 4. Logistic regression models explaining exposure of 196 white-tailed deer (Odocoileus virginianus) to Leptospira interrogans pomona from two sites in Wisconsin, USA, 2010–2013.

Model a	AICc b	ΔAICc c	w i d	K e	ROC f
LT	184.89	0.00	0.278	2	0.64
CS, LT, CS*LT	185.61	0.72	0.194	4	0.66
IBR, PI3, LT	186.44	1.55	0.128	4	0.63
LT, Age	186.71	1.82	0.112	3	0.66
LT, CY, LT*CY	187.09	2.20	0.093	6	0.70
CS, Age, LT	187.10	2.21	0.092	4	0.67
CS	188.49	3.60	0.046	2	0.61
CS, Age	190.46	5.57	0.017	3	0.62
CS, CY	191.37	6.48	0.011	4	0.63
CS, Age, Sex	192.20	7.31	0.007	4	0.61
Global (Age, Sex, CS, LT, CY, PI3, IBR)	192.61	7.72	0.006	9	0.69
Sex	192.77	7.87	0.005	2	0.55
Site, Age, Sex, Site*Age*Sex	193.17	8.28	0.004	5	0.62
PI3	194.38	9.49	0.002	2	0.50
PI3, IBR, PI3*IBR	194.65	9.76	0.002	4	0.53

^aLT = land type (public vs. private); CS = capture site; IBR = exposure to infectious bovine rhinotracheitis virus; PI3 = exposure to parainfluenza 3 virus; Age = deer age; Year = capture year; Sex = male or female.

^bAkaike’s Information Criterion corrected for small sample size [31].

^cDifference in AIC_c relative to minimum AIC.

^dAkaike weight [31].

^eNumber of parameters.

^fArea under the receiver operating characteristic curve.