Hello,

 
I'd like to compare the predictive power of two independent simple 
regression models, which relate to data sets with different numbers of 
points (n1 and n2). I think I could use a F-test to compare both 
residual variances, but I don't know whether it's a good idea or not. 
To my opinion, the numbers of degrees of freedom for the F-test would 
be respectively the number of degrees of freedom of the greater 
residual variance (in the numerator of the F-statistic), e.g. n1-2, 
and the number of degrees of freedom for the smaller residual variance 
(in the denominator of the F-statistic), e.g. n2-2 ; but I'm not sure 
about what quantities to put in the numerator and the denominator of 
the F-statistic. Indeed, for two sample variances, the formula to 
calculate the F-statistic would be (n1*s1²/(n1-1))/(n2*s2²/(n2-1)), 
with s1 and s2 being sample variances, but what happens when variances 
are residual variances coming from two independent simple regression 
analyses ? Is there any function in R that would enable me to perform this kind of test ?

Could anyone help me to solve these issues ? 

Thank you in advance, 
Scoubi.
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