[R] extracting significance test for individual lm() parameters after using by

Jeff Newmiller jdnewmil at dcn.davis.CA.us
Sun Jan 25 04:04:12 CET 2015

R-square is often a poor indicator of whether a model is appropriate or not. While it is possible that there exists a package that implements your algorithm (which you might find using the sos package), I would recommend that you get some advice from an expert on how to approach this subject, and this list is not a good place for studying statistics theory (read the Posting Guide). You might try stats.stackexchange. com. 
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Sent from my phone. Please excuse my brevity.

On January 24, 2015 6:01:59 PM PST, "Moxley, Jerad" <moxley at psy.fsu.edu> wrote:
>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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>and provide commented, minimal, self-contained, reproducible code.

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