Four Parameters: Categorical

With data from the National Election Survey, we are trying to understand the relationship between voter preference of the top 3 candidates and sex in the 1992 Presidential election. However, stability may not hold because voters voted at different times, even in the fall of 1992. We created a categorical, multinomial logistic regression model with sex predicting voter preference. We found that male voters were negatively related with Clinton, suggesting that male voters were less likely to vote for Clinton. Overall, Women were more likely to vote for Clinton while men were more likely to vote for Perot. Expected percentage of votes for Bush were similar for women and men, with similar amounts of variability.

\[\begin{aligned} \rho_{clinton} &=& \frac{e^{\beta_{0, clinton} + \beta_{1, clinton} male}}{1 + e^{\beta_{0, clinton} + \beta_{1, clinton} male}}\\ \rho_{perot} &=& \frac{e^{\beta_{0, perot} + \beta_{1, perot} male}}{1 + e^{\beta_{0, perot} + \beta_{1, perot} male}}\\ \rho_{bush} &=& 1 - \rho_{clinton} - \rho_{perot} \end{aligned}\]

Characteristic	Beta	95% CI 1
muClinton_(Intercept)	0.45	0.31, 0.60
muPerot_(Intercept)	-0.86	-1.1, -0.64
muClinton_sexMale	-0.25	-0.48, -0.04
muPerot_sexMale	0.42	0.14, 0.71
1 CI = Credible Interval