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L
OGISTIC
R
EGRESSION
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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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