\begin{Schunk}
\begin{Sinput}
 rmsFmiTitanic <- fit.mult.impute( survived ~ pclass + sex + age, glm, family=binomial(link=logit), rmsImputeTitanic, data= titanic, fit.reps=TRUE)
\end{Sinput}
\begin{Soutput}
Variance Inflation Factors Due to Imputation:

(Intercept)   pclass2nd   pclass3rd     sexmale         age 
        2.8         2.1         4.5         1.9         2.5 

Rate of Missing Information:

(Intercept)   pclass2nd   pclass3rd     sexmale         age 
       0.65        0.53        0.78        0.48        0.59 

d.f. for t-distribution for Tests of Single Coefficients:

(Intercept)   pclass2nd   pclass3rd     sexmale         age 
         22          32          15          39          26 

The following fit components were averaged over the 10 model fits:

  fitted.values linear.predictors 
\end{Soutput}
\begin{Sinput}
 summary(rmsFmiTitanic)
\end{Sinput}
\begin{Soutput}
Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.143  -0.735  -0.386   0.680   2.901  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.24518    0.30409   13.96  < 2e-16 ***
pclass2nd   -1.37042    0.20975   -6.53  6.4e-11 ***
pclass3rd   -2.85903    0.19864  -14.39  < 2e-16 ***
sexmale     -2.37998    0.15689  -15.17  < 2e-16 ***
age         -0.05526    0.00569   -9.71  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 1680.1  on 1312  degrees of freedom
Residual deviance: 1148.6  on 1308  degrees of freedom
AIC: 1159

Number of Fisher Scoring iterations: 5
\end{Soutput}
\end{Schunk}
