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Candidate Gender and Voting in Statewide Elections: Evidence from Ohio
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Table 6. Vote Choice for Ohio Supreme Court
Model 1
Model 2
1
Model 3
2
Female-
Female
Male-
Female
Female-
Female
Male-
Female
Female-
Female
Male-
Female
Baseline gender preference
-.113
(.301)
.467
(.293)
-.322
(.341)
.261
(.330)
-.094
(.330)
.541
a
(.316)
Party identification
-.638**
(.124)
-.590**
(.121)
-.672**
(.137)
-.685**
(.141)
-.641**
(.139)
-.562**
(.138)
Vote for governor
.862
(.544)
1.246*
(.507)
.757
(.592)
1.055*
(.516)
.730
(.572)
1.025
a
(.570)
Intercept
2.079**
(.748)
1.862**
(.706)
1.130
(1.534)
2.689
a
(1.625)
3.679*
(1.699)
4.165*
(1.781)
n
171
184
167
179
154 167
χ
2
92.52**
(3 df)
99.05**
(3 df)
94.13**
(8 df)
103.69**
(8 df)
82.53**
(8 df)
90.42**
(8 df)
Initial
log
likelihood -116.98 -125.08 -113.56 -121.71 -105.44 -113.88
Final
log
likelihood -70.71 -75.56 -66.50 -69.87 -64.18 -68.67
a
p
≤
.10, * p
≤
.05, ** p
≤
.01
Note: Cell entries are estimates from a logistic regression model with standard errors in parentheses. The dependent variable is coded 1 for Republican and 0 for Democrat. The baseline preference is coded 1 for prefer a woman, 0 for neutral, and –1 for prefer a man. Party identification is coded 1 through 7 from strong Republican to strong Democrat. Vote for governor is coded 1 for Republican, 0 for Democrat.
1
Model 2 includes controls for gender, age, education, religiosity, and race.
2
Model 3 includes controls for government spending, abortion, whether change is needed in politics,
political knowledge, and attention to the election. Source: TOPS 2002.
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| | Authors: Sanbonmatsu, Kira. |
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22
Table 6. Vote Choice for Ohio Supreme Court
Model 1
Model 2
1
Model 3
2
Female-
Female
Male-
Female
Female-
Female
Male-
Female
Female-
Female
Male-
Female
Baseline gender
preference
-.113
(.301)
.467
(.293)
-.322
(.341)
.261
(.330)
-.094
(.330)
.541
a
(.316)
Party identification
-.638**
(.124)
-.590**
(.121)
-.672**
(.137)
-.685**
(.141)
-.641**
(.139)
-.562**
(.138)
Vote for governor
.862
(.544)
1.246*
(.507)
.757
(.592)
1.055*
(.516)
.730
(.572)
1.025
a
(.570)
Intercept
2.079**
(.748)
1.862**
(.706)
1.130
(1.534)
2.689
a
(1.625)
3.679*
(1.699)
4.165*
(1.781)
n
171
184
167
179
154 167
χ
2
92.52**
(3 df)
99.05**
(3 df)
94.13**
(8 df)
103.69**
(8 df)
82.53**
(8 df)
90.42**
(8 df)
Initial
log
likelihood -116.98 -125.08 -113.56 -121.71 -105.44 -113.88
Final
log
likelihood -70.71 -75.56 -66.50 -69.87 -64.18 -68.67
a
p
≤
.10, * p
≤
.05, ** p
≤
.01
Note: Cell entries are estimates from a logistic regression model with standard errors in parentheses. The
dependent variable is coded 1 for Republican and 0 for Democrat. The baseline preference is coded 1 for
prefer a woman, 0 for neutral, and –1 for prefer a man. Party identification is coded 1 through 7 from
strong Republican to strong Democrat. Vote for governor is coded 1 for Republican, 0 for Democrat.
1
Model 2 includes controls for gender, age, education, religiosity, and race.
2
Model 3 includes controls for government spending, abortion, whether change is needed in politics,
political knowledge, and attention to the election.
Source: TOPS 2002.
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