columnames changes behaviour of formula
P.S. It really is sloppy code to mix variables from the global environment with those inside a data frame. I.e.: coef(lm(d ~ -1 + (.)^2, data = x)) the only time I think it makes sense to have different objects for the outcome and predictors are when for speed purposes, you are using a low level function, such as lm.fit or fastLmPure from the RcppEigen package.
On Thu, May 24, 2012 at 9:46 PM, Joshua Wiley <jwiley.psych at gmail.com> wrote:
Hi Robin, Seems like the intended behavior to me. ?From the docs: "There are two special interpretations of '.' in a formula. ?The usual one is in the context of a 'data' argument of model fitting functions and means 'all columns not otherwise in the formula' " d is in the formula so the only column not in the formula is nd. ?the (.)^2 asks for all two way interactions, but with only one variable, there are none. What were you expecting? Josh On Thu, May 24, 2012 at 9:25 PM, robin hankin <hankin.robin at gmail.com> wrote:
Hello. precompiled R-2.15.0, svn58871, macosx 10.7.4.
I have discovered that defining column names of a dataframe can alter the
behaviour of lm():
d <- c(4,7,6,4)
x <- data.frame(cbind(0:3,5:2))
coef(lm(d~ -1 + (.)^2,data=x))
? X1 ? ?X2 X1:X2
-1.77 ?0.83 ?1.25
R>
R>
OK, so far so good. ?But change the column names of 'x' and the behaviour
changes:
colnames(x) <- c("d","nd") ? # 'd' == 'death' and 'nd' == 'no death'
coef(lm(d~ -1 + (.)^2,data=x))
? ? ? nd
0.2962963
I am not sure if this is consistent with the special meaning of '.'
described under ?formula.
Is this the intended behaviour?
--
Robin Hankin
Uncertainty Analyst
hankin.robin at gmail.com
? ? ? ?[[alternative HTML version deleted]]
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-- Joshua Wiley Ph.D. Student, Health Psychology Programmer Analyst II, Statistical Consulting Group University of California, Los Angeles https://joshuawiley.com/
Joshua Wiley Ph.D. Student, Health Psychology Programmer Analyst II, Statistical Consulting Group University of California, Los Angeles https://joshuawiley.com/