Run another multiple regression with the previous 4 predictors and the 4 other predictors - hc.law, economy, wall, and isis. Evaluate the overall model and identify any statistically significant relationships.
Using the 2016 ANES, replicate the analysis with feelings towards Trump using feelings towards Hillary
Clinton. The variable for Clinton is V161086 and use the same 8 predictor variables.
summary(model.2 <- lm(clinton ~ gender + education + pid.num + ideology.num +
hc.law.num + economy.num + wall.num + isis.num, data=nes2))
Call:
lm(formula = clinton ~ gender + education + pid.num + ideology.num +
hc.law.num + economy.num + wall.num + isis.num, data = nes2)
Residuals:
Min 1Q Median 3Q Max
-74.255 -12.017 -0.559 12.498 100.638
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 56.3224 5.2530 10.722 < 2e-16 ***
gender1. Female 2.9070 1.1781 2.467 0.0137 *
education -0.3011 0.2667 -1.129 0.2591
pid.num -6.9608 0.4302 -16.181 < 2e-16 ***
ideology.num -0.4538 0.5474 -0.829 0.4073
hc.law.num 3.5386 0.3168 11.169 < 2e-16 ***
economy.num 3.8651 0.6743 5.732 1.25e-08 ***
wall.num -1.6545 0.3109 -5.321 1.23e-07 ***
isis.num -0.2914 0.3014 -0.967 0.3337
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 20.22 on 1204 degrees of freedom
Multiple R-squared: 0.6402, Adjusted R-squared: 0.6379
F-statistic: 267.8 on 8 and 1204 DF, p-value: < 2.2e-16
confint(model.2, level=.95)
2.5 % 97.5 %
(Intercept) 46.0163685 66.6285020
gender1. Female 0.5955658 5.2183826
education -0.8243674 0.2221068
pid.num -7.8047580 -6.1167445
ideology.num -1.5277532 0.6202416
hc.law.num 2.9169790 4.1601661
economy.num 2.5422703 5.1880177
wall.num -2.2644603 -1.0444911
isis.num -0.8827097 0.2998143
The overall model is again statistically significant and the adjusted R2 is now .64 indicating that our model explains roughly 64% of the variance in feelings towards Clinton. We now find that gender is significant, but political ideology is not, when controlling for the four additional predictors. The positive coefficient for gender implies that women have warmer feelings toward Clinton than men. The coefficients for Obamacare and the economy are both positive indicating that as respondents’ support for the health care law and positive evaluation of the economy increases their feelings towards Clinton increase. The negative coefficient for the wall with Mexico suggests that as respondents’ support of building a wall increases their feelings for Clinton decrease.
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