Dear R-devel list members,
This is an observation about how logical variables in models are handled,
followed by questions.
As a general matter, character variables and logical variables are treated as if
they were factors when they appear on the RHS of a model formula; for example:
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> set.seed(123)
> c <- sample(letters[1:3], 10, replace=TRUE)
> f <- as.factor(sample(LETTERS[1:3], 10, replace=TRUE))
> L <- sample(c(TRUE, FALSE), 10, replace=TRUE)
> y <- rnorm(10)
> options(contrasts=c("contr.sum", "contr.poly"))
> mod <- lm(y ~ c + f + L)
> model.matrix(mod)
(Intercept) c1 c2 f1 f2 L1
1 1 1 0 -1 -1 1
2 1 -1 -1 0 1 1
3 1 0 1 -1 -1 1
4 1 -1 -1 0 1 1
5 1 -1 -1 1 0 1
6 1 1 0 -1 -1 1
7 1 0 1 1 0 1
8 1 -1 -1 1 0 1
9 1 0 1 1 0 -1
10 1 0 1 -1 -1 -1
attr(,"assign")
[1] 0 1 1 2 2 3
attr(,"contrasts")
attr(,"contrasts")$c
[1] "contr.sum"
attr(,"contrasts")$f
[1] "contr.sum"
attr(,"contrasts")$L
[1] ?contr.sum"
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But logical variables don?t appear in the $xlevels component of the objects
created by lm() and similar functions:
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> mod$xlevels
$c
[1] "a" "b" "c"
$f
[1] "A" "B" ?C"
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Why the discrepancy? It?s true that the level-set (i.e., TRUE, FALSE) for a
logical ?factor? is known, but examining the $levels component is a simple way
to detect variables treated as factors in the model. For example, I?d argue that
.getXlevels() returns misleading information:
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> .getXlevels(terms(mod), model.frame(mod))
$c
[1] "a" "b" "c"
$f
[1] "A" "B" ?C"
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An alternative for detecting ?factors? is to examine the 'contrasts'
attribute of the model matrix, although that doesn?t produce levels:
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> names(attr(model.matrix(mod), "contrasts"))
[1] "c" "f" "L"
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Is there are argument against making the treatment of logical variables
consistent with that of factors and character variables? Comments?
Best,
John
-------------------------------------------------
John Fox, Professor Emeritus
McMaster University
Hamilton, Ontario, Canada
Web: http::/socserv.mcmaster.ca/jfox
