\begin{Schunk}
\begin{Sinput}
 logitpred <- predict(bushideolrm5, type="response")
 probitpred <- predict(bushideoProbit5, type="response")
 plot(logitpred, probitpred, xlab="Predicted Probabilities from Logit Model", ylab="Predicted Probabilties from Probit Model", main="Scatterplot of Predictions from Logit and Probit")
 pmod1 <- lm(probitpred ~ logitpred)
 summary(pmod1)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = probitpred ~ logitpred)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.03754 -0.01067  0.00039  0.00623  0.05724 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 0.009604   0.000842    11.4   <2e-16 ***
logitpred   0.988270   0.001219   810.9   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.0141 on 798 degrees of freedom
Multiple R-squared:  0.999,	Adjusted R-squared:  0.999 
F-statistic: 6.58e+05 on 1 and 798 DF,  p-value: <2e-16
\end{Soutput}
\begin{Sinput}
 abline(pmod1, col="red", lwd=2)
 legend("topleft", legend=c("OLS regression"), col="red", lwd=2)
\end{Sinput}
\end{Schunk}
