Table 6.

Logistic regression models for the association between attractiveness and the odds of arrest for males and females.

	Males (N = 3960)		Males (N = 3770)		Females (N = 4832)		Females (N = 4714)
	Coeff	OR	Coeff	OR	Coeff	OR	Coeff	OR
Predictor variables
Attractiveness	−.103	0.902	−.072	0.930	−.214	0.807*	−.162	0.850*
	(.061)		(.066)		(.060)		(.066)
Criminal involvement	—		.383	1.465*	—		.450	1.569*
			(.040)				(.056)
Controls
Age	.039	1.041*	.074	1.077*	−.055	0.946*	−.025	0.975
	(.021)		(.023)		(.023)		(.025)
Race	.125	1.133	.166	1.181*	.200	1.221*	.114	1.120
	(.080)		(.089)		(.100)		(.096)
SES	.467	1.596*	.536	1.709*	.456	1.578*	.457	1.579*
	(.193)		(.219)		(.187)		(.198)

Note. OR = odds ratio; coeff = coefficient; SES = socioeconomic status.

Standard errors in parentheses.

*p < .05.