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37
L
OGISTIC
R
EGRESSION
:
M
ODEL
4
glm(formula = vote ~ approve + pid + age + income + educ + t1 +
t2 + t3 + t4 + born + t1 * born + t2 * born + t3 * born +
t4 * born, family = binomial(link = "logit"))
coef.est coef.sd
(Intercept) 1.09 2.00
approve 2.53 0.20
pid -1.89 0.20
age 0.00 0.01
income -0.07 0.08
educ 0.25 0.12
t1 -2.51 2.08
t2 -0.73 2.50
t3 0.47 2.42
born -1.24 1.15
t1:born 1.20 1.23
t2:born 0.44 1.55
t3:born -0.02 1.66
n = 935, k = 13
residual deviance = 330.1, null deviance = 1183.7 (difference =
853.6)
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