[R] anova.lm F test confusion

[msteane]

I am using anova.lm to compare 3 linear models.  Model 1 has 1 variable,
model 2 has 2 variables and model 3 has 3 variables.  All models are fitted
to the same data set.

anova.lm(model1,model2) gives me:

  Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
1    135 245.38                                  
2    134 184.36  1    61.022 44.354 6.467e-10 ***

anova.lm(model1,model2,model3) gives me:

  Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
1    135 245.38                                  
2    134 184.36  1    61.022 50.182 7.355e-11 ***
3    133 161.73  1    22.628 18.609 3.105e-05 ***


Why aren't the 2nd row F values from each of the anova tables the same??? I
thought in each case the 2nd row is comparing model 2 to model 1?  

I figured out that for anova.lm(model1,model2) 
F(row2)=Sum of Sq(row2)/MSE of Model 2 

and for anova.lm(model1,model2,model3)
 F(row2)=Sum of Sq(row 2)/MSE of Model 3  <-- I don't get why the MSE of
model 3 is being included if we're comparing Model 2 to Model 2



Any help/explanations would be appreciated! 

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