> donner.mod1 <- glm(formula = survive ~ age + male + agemale, family=binomial("logit"))
> 
> summary(donner.mod1)

Call:
glm(formula = survive ~ age + male + agemale, family = binomial("logit"))

Deviance Residuals: 
     Min        1Q    Median        3Q       Max  
-1.94094  -0.98791   0.59593   1.08709   1.75791  

Coefficients:
             Estimate Std. Error z value Pr(>|z|)  
(Intercept)  1.758892   0.689385  2.5514  0.01073 *
age         -0.040194   0.028316 -1.4195  0.15575  
male        -1.413206   0.843239 -1.6759  0.09375 .
agemale      0.007823   0.034578  0.2262  0.82101  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 122.829  on 88  degrees of freedom
Residual deviance: 109.037  on 85  degrees of freedom
AIC: 117.037

Number of Fisher Scoring iterations: 4

> 
> anova(donner.mod1, test="Chisq")
Analysis of Deviance Table

Model: binomial, link: logit

Response: survive

Terms added sequentially (first to last)


        Df Deviance Resid. Df Resid. Dev P(>|Chi|)   
NULL                       88    122.829             
age      1  6.65195        87    116.177 0.0099047 **
male     1  7.08851        86    109.089 0.0077580 **
agemale  1  0.05126        85    109.037 0.8208817   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> donner.mod2 <- glm(formula = survive ~ age + male, family=binomial("logit"))
> 
> summary(donner.mod2)

Call:
glm(formula = survive ~ age + male, family = binomial("logit"))

Deviance Residuals: 
     Min        1Q    Median        3Q       Max  
-1.89847  -0.98268   0.61993   1.07006   1.79434  

Coefficients:
             Estimate Std. Error z value Pr(>|z|)   
(Intercept)  1.656807   0.510036  3.2484 0.001161 **
age         -0.034992   0.016360 -2.1389 0.032446 * 
male        -1.258990   0.488098 -2.5794 0.009898 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 122.829  on 88  degrees of freedom
Residual deviance: 109.089  on 86  degrees of freedom
AIC: 115.089

Number of Fisher Scoring iterations: 4

> 
> anova(donner.mod2, test="Chisq")
Analysis of Deviance Table

Model: binomial, link: logit

Response: survive

Terms added sequentially (first to last)


     Df Deviance Resid. Df Resid. Dev P(>|Chi|)   
NULL                    88    122.829             
age   1  6.65195        87    116.177 0.0099047 **
male  1  7.08851        86    109.089 0.0077580 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
>