m...@biostat.mgh.harvard.edu wrote:
> Full_Name: Marek Ancukiewicz
> Version: 2.10.1
> OS: Linux
> Submission from: (NULL) (74.0.49.2)
>
>
> Both cor() and cor.test() incorrectly handle ordered variables with
> method="kendall", cor() incorrectly handles ordered variables for
> method="spearman" (method="person" always works correctly, while
> method="spearman" works for cor.test, but not for cor()).
>
> In erroneous calculations these functions ignore the inherent ordering
> of the ordered variable (e.g., '9'<'10'<'11') and instead seem to assume
> an alphabetic ordering ('10'<'11'<'9').
Strictly speaking, not a bug, since the documentation has
x: a numeric vector, matrix or data frame.
respectively
x, y: numeric vectors of data values. ‘x’ and ‘y’ must have the
same length.
so noone ever claimed that class "ordered" variables should work.
However, the root cause is that as.vector on a factor variable (ordered
or not) converts it to a character vector, hence
> rank(as.vector(as.ordered(9:11)))
[1] 3 1 2
Looks like a simple fix would be to use as.vector(x, "numeric") inside
the definition of cor().
>> cor(9:11,1:3,method="k")
> [1] 1
>> cor(as.ordered(9:11),1:3,method="k")
> [1] -0.3333333
>> cor.test(as.ordered(9:11),1:3,method="k")
>
> Kendall's rank correlation tau
>
> data: as.ordered(9:11) and 1:3
> T = 1, p-value = 1
> alternative hypothesis: true tau is not equal to 0
> sample estimates:
> tau
> -0.3333333
>
>> cor(9:11,1:3,method="s")
> [1] 1
>> cor(as.ordered(9:11),1:3,method="s")
> [1] -0.5
>> cor.test(as.ordered(9:11),1:3,method="s")
>
> Spearman's rank correlation rho
>
> data: as.ordered(9:11) and 1:3
> S = 0, p-value = 0.3333
> alternative hypothesis: true rho is not equal to 0
> sample estimates:
> rho
> 1
>
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--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907
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