The classic way to test for better fit with an additional variable is to use
the anova() function. The model must have the suspect variable listed last
into your model. The anova() function will give you the correct sequential
decomposition of your model effects and their conditional (F or t)
I would suggest doing an F-test.A descrition is given here:
http://www.graphpad.com/curvefit/2_models__1_dataset.htm.
The method is valid becasue one of your models is a subset of another.
Correct use of the anova function does indeed perform this test.
For example:
data(airquality)
lm1<-l
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