I’m trying to test what growth functions best fit individual subjects. I’m
wanting compare linear, quadratic, cubic etc. Here is the example from the
cubic curve.
b3a<-by(c,id,function(x) lm(w~agec+ageq+agecub,data=x))
I can get quiet a bit of information out of sapply(b3a,summary) but it reports
something like this for each person
37
call Expression
terms Expression
residuals Numeric,62
coefficients Numeric,16
aliased Logical,4 4
sigma 67.05895
df Integer,3
r.squared 0.9822921
adj.r.squared 0.9813762
fstatistic Numeric,3
cov.unscaled Numeric,16
I could obviously compute by hand the r squared change and then compute a p
value based for what the partial r is for the variable but I’d like to have a
simpler solution to it. Can I get the information or is there an package that I
should download that will do what I’m trying to do much simpler?
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