Table 3 Predicting correctly identifying... | Emerald Publishing

Table 3

Predicting correctly identifying the officer’s gender

	Correct response
Constant	0.81*
Constant	(0.36)
Age	0.01*
Age	(0.00)
Woman	0.08
Woman	(0.15)
Race – White	−0.14
Race – White	(0.17)
Education	−0.03
Education	(0.09)
Income	0.00
Income	(0.02)
Political Ideology	−0.04
Political Ideology	(0.04)
Party ID – Independent	0.15
Party ID – Independent	(0.21)
Party ID – Republican	0.14
Party ID – Republican	(0.28)
T1 – Male	−0.75**
T1 – Male	(0.16)
T2 – Female	2.39**
T2 – Female	(0.32)
Observations	1,193
Log Likelihood	−546.33
Akaike Inf. Crit	1114.65

	Correct response
Constant	0.81*
Constant	(0.36)
Age	0.01*
Age	(0.00)
Woman	0.08
Woman	(0.15)
Race – White	−0.14
Race – White	(0.17)
Education	−0.03
Education	(0.09)
Income	0.00
Income	(0.02)
Political Ideology	−0.04
Political Ideology	(0.04)
Party ID – Independent	0.15
Party ID – Independent	(0.21)
Party ID – Republican	0.14
Party ID – Republican	(0.28)
T1 – Male	−0.75**
T1 – Male	(0.16)
T2 – Female	2.39**
T2 – Female	(0.32)
Observations	1,193
Log Likelihood	−546.33
Akaike Inf. Crit	1114.65

Note(s): *p < 0.05. **p < 0.01. Standard error in parentheses; unstandardized coefficients

Source(s): Authors’ own work