\begin{Schunk}
\begin{Sinput}
 for(i in 1:length(rmsFmiTitanic$fits)) print(summary(rmsFmiTitanic$fits[[i]]))
\end{Sinput}
\begin{Soutput}
Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.318  -0.722  -0.375   0.624   3.065  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.27977    0.33643   12.72  < 2e-16 ***
pclass2nd   -1.30687    0.21447   -6.09  1.1e-09 ***
pclass3rd   -2.77282    0.20172  -13.75  < 2e-16 ***
sexmale     -2.34844    0.16246  -14.46  < 2e-16 ***
age         -0.05740    0.00612   -9.38  < 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


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.488  -0.657  -0.350   0.629   2.976  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.70439    0.32223   14.60  < 2e-16 ***
pclass2nd   -1.69747    0.21563   -7.87  3.5e-15 ***
pclass3rd   -2.86445    0.20043  -14.29  < 2e-16 ***
sexmale     -2.11856    0.16525  -12.82  < 2e-16 ***
age         -0.06367    0.00564  -11.29  < 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: 1698.3  on 1312  degrees of freedom
Residual deviance: 1103.0  on 1308  degrees of freedom
AIC: 1113

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.522  -0.584  -0.326   0.549   2.669  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  5.15318    0.36868   13.98  < 2e-16 ***
pclass2nd   -1.68279    0.23263   -7.23  4.7e-13 ***
pclass3rd   -3.72679    0.23826  -15.64  < 2e-16 ***
sexmale     -2.52675    0.17290  -14.61  < 2e-16 ***
age         -0.06950    0.00684  -10.16  < 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: 1691.9  on 1312  degrees of freedom
Residual deviance: 1050.4  on 1308  degrees of freedom
AIC: 1060

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.573  -0.648  -0.351   0.585   2.765  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.26266    0.31396   13.58  < 2e-16 ***
pclass2nd   -1.43351    0.21260   -6.74  1.6e-11 ***
pclass3rd   -3.00432    0.21207  -14.17  < 2e-16 ***
sexmale     -2.47417    0.16366  -15.12  < 2e-16 ***
age         -0.05497    0.00572   -9.61  < 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: 1689.4  on 1312  degrees of freedom
Residual deviance: 1108.5  on 1308  degrees of freedom
AIC: 1119

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.523  -0.672  -0.375   0.578   2.588  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.08354    0.31901   12.80   <2e-16 ***
pclass2nd   -1.46783    0.21463   -6.84    8e-12 ***
pclass3rd   -2.91258    0.20744  -14.04   <2e-16 ***
sexmale     -2.50116    0.16286  -15.36   <2e-16 ***
age         -0.04957    0.00576   -8.61   <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: 1678.8  on 1312  degrees of freedom
Residual deviance: 1119.7  on 1308  degrees of freedom
AIC: 1130

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.637  -0.750  -0.404   0.616   2.819  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.16399    0.33749   12.34  < 2e-16 ***
pclass2nd   -1.38169    0.21875   -6.32  2.7e-10 ***
pclass3rd   -2.82804    0.20494  -13.80  < 2e-16 ***
sexmale     -2.30791    0.16029  -14.40  < 2e-16 ***
age         -0.05521    0.00624   -8.85  < 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: 1686.8  on 1312  degrees of freedom
Residual deviance: 1172.5  on 1308  degrees of freedom
AIC: 1182

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.810  -0.747  -0.186   0.629   2.685  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)   4.0348     0.2995   13.47  < 2e-16 ***
pclass2nd    -1.2541     0.2085   -6.01  1.8e-09 ***
pclass3rd    -2.4904     0.1952  -12.76  < 2e-16 ***
sexmale      -2.2320     0.1633  -13.66  < 2e-16 ***
age          -0.0525     0.0056   -9.37  < 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: 1694.5  on 1312  degrees of freedom
Residual deviance: 1100.1  on 1308  degrees of freedom
AIC: 1110

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.497  -0.678  -0.323   0.529   2.812  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  4.23938    0.34465   12.30  < 2e-16 ***
pclass2nd   -1.28286    0.22106   -5.80  6.5e-09 ***
pclass3rd   -2.95459    0.21243  -13.91  < 2e-16 ***
sexmale     -2.62029    0.16949  -15.46  < 2e-16 ***
age         -0.05305    0.00634   -8.36  < 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: 1669.2  on 1312  degrees of freedom
Residual deviance: 1075.9  on 1308  degrees of freedom
AIC: 1086

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.417  -0.693  -0.330   0.607   2.893  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  3.75758    0.29209   12.86  < 2e-16 ***
pclass2nd   -0.97306    0.20516   -4.74  2.1e-06 ***
pclass3rd   -2.36932    0.19073  -12.42  < 2e-16 ***
sexmale     -2.34050    0.15930  -14.69  < 2e-16 ***
age         -0.04948    0.00538   -9.19  < 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: 1133.4  on 1308  degrees of freedom
AIC: 1143

Number of Fisher Scoring iterations: 5


Call:
fitter(formula = formula, family = ..1, data = completed.data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-2.458  -0.696  -0.376   0.618   2.838  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  3.77253    0.30409   12.41  < 2e-16 ***
pclass2nd   -1.22397    0.20975   -5.84  5.4e-09 ***
pclass3rd   -2.66704    0.19864  -13.43  < 2e-16 ***
sexmale     -2.33004    0.15689  -14.85  < 2e-16 ***
age         -0.04719    0.00569   -8.30  < 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}
