\begin{Schunk}
\begin{Sinput}
 nes2002$educf2 <- combineLevels(nes2002$educf, levs=c(5,6,7),  "Higher Ed")
\end{Sinput}
\begin{Soutput}
The original levels Elem. Some HS HS Some coll. AA BA Grad 
have been replaced by Elem. Some HS HS Some coll. Higher Ed 
\end{Soutput}
\begin{Sinput}
 table("educ: reduced" = nes2002$educf2, "educ: 7 categories" = nes2002$educf, exclude = NULL)
\end{Sinput}
\begin{Soutput}
             educ: 7 categories
educ: reduced Elem. Some HS  HS Some coll.  AA  BA Grad <NA>
   Elem.         36       0   0          0   0   0    0    0
   Some HS        0      70   0          0   0   0    0    0
   HS             0       0 399          0   0   0    0    0
   Some coll.     0       0   0        313   0   0    0    0
   Higher Ed      0       0   0          0 155 347  178    0
   <NA>           0       0   0          0   0   0    0   13
\end{Soutput}
\begin{Sinput}
 bushlogit6c <- glm(bushvote ~ V023010 + ideoln + partyid + educf2 + useconn, data=nes2002, family=binomial(link=logit))
 summary(bushlogit6c)
\end{Sinput}
\begin{Soutput}
Call:
glm(formula = bushvote ~ V023010 + ideoln + partyid + educf2 + 
    useconn, family = binomial(link = logit), data = nes2002)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.7599  -0.2879   0.1383   0.3350   3.2901  

Coefficients:
                  Estimate Std. Error z value Pr(>|z|)    
(Intercept)      -6.952875   1.387320  -5.012 5.39e-07 ***
V023010           0.065777   0.007869   8.359  < 2e-16 ***
ideoln            0.390721   0.111757   3.496 0.000472 ***
partyidD         -2.662545   0.332474  -8.008 1.16e-15 ***
partyidR          1.257030   0.335806   3.743 0.000182 ***
educf2Some HS     1.440676   1.337084   1.077 0.281268    
educf2HS          2.007157   1.098655   1.827 0.067711 .  
educf2Some coll.  2.457434   1.110353   2.213 0.026884 *  
educf2Higher Ed   1.501258   1.076607   1.394 0.163186    
useconn          -0.094573   0.127159  -0.744 0.457038    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 1066.72  on 774  degrees of freedom
Residual deviance:  394.69  on 765  degrees of freedom
  (736 observations deleted due to missingness)
AIC: 414.69

Number of Fisher Scoring iterations: 6
\end{Soutput}
\end{Schunk}
