[R] stratified Wilcoxon available?

[Peter Dalgaard]

Torsten Hothorn <Torsten.Hothorn at rzmail.uni-erlangen.de> writes:

> On Mon, 29 Aug 2005, Peter Dalgaard wrote:
> 
> > Torsten Hothorn <Torsten.Hothorn at rzmail.uni-erlangen.de> writes:
> >
> > > > Dear All,
> > > >
> > > > is there a stratified version of the Wilcoxon test (also known as van
> > > > Elteren test) available in R?
> > >
> > > you can plug it together using the `coin' infrastructure (see the
> > > examples in the manual and vignette).
> >
> > I managed to dig out our old code, and patched it up loosely to fit
> > versions of R later than 0.62 (the trend test code still seems
> > broken). Use at own risk. The usage is fairly straightforward:
> >
> > > SKruskal.test(y~g1|g2)
> >
> >         Kruskal-Wallis stratified rank sum test
> >
> > data:  y , group:  g1 , strata:  g2
> > K = 3.1486, df = 3, p-value = 0.3693
> >
> 
> the conditional version of the above test can be computed as follows:
> 
> R> library("coin")
> R> set.seed(290875)
> R> mydf <- data.frame(y = rnorm(90), x = gl(3, 30)[sample(1:90)], b = gl(3, 30))
> R>
> R> ### with global ranks, i.e., ranking without using the blocks
> R> kruskal_test(y ~ x | b, data = mydf)
> 
>         Asymptotic Kruskal-Wallis Test
> 
> data:  y by groups 1, 2, 3
>          stratified by b
> T = 0.5242, df = 2, p-value = 0.7694
> 
> R>
> R> ### with _blockwise_ ranking and quadratic form of the test statistic
> R> independence_test(y ~ x | b, data = mydf, ytrafo = function(data) trafo(data,
> +                   numeric_trafo = rank, block = mydf$b), teststat = "quad")
> 
>         Asymptotic General Independence Test
> 
> data:  y by groups 1, 2, 3
>          stratified by b
> T = 0.3824, df = 2, p-value = 0.826
> 
> R>
> R> ### the same
> R> SKruskal.test(y ~ x | b, data = mydf)
> 
>         Kruskal-Wallis stratified rank sum test
> 
> data:  y , group:  x , strata:  b
> K = 0.3824, df = 2, p-value = 0.826
> 
> R>
> R>
> R>
> R> ### trend test (using scores 1, 2, 3)
> R> independence_test(y ~ x | b, data = mydf, ytrafo = function(data) trafo(data,
> +                   numeric_trafo = rank, block = mydf$b), teststat = "quad",
> +                   scores = list(x = 1:3))
> 
>         Asymptotic General Independence Test
> 
> data:  y by groups 1 < 2 < 3
>          stratified by b
> T = 0.0264, df = 1, p-value = 0.871
> 
> R>
> R> ### hm.
> R> SKruskal.test(y ~ x | b, data = mydf, trend = TRUE)
> Error in SKruskal.test(y ~ x | b, data = mydf, trend = TRUE) :
>         subscript out of bounds
> 
> Best,
> 
> Torsten

Nice to see that the old code made sense. A bit surprising that it
gives _exactly_ the same result as the blockwise ranking in coin...
Perhaps introduce some ties? (round(y,1) is usually effective).

The trend test is easily fixed: just spell "t value" without capital V
as we do nowadays. This gives


> SKruskal.test(y ~ x | b, data = mydf, trend = TRUE)

        Kruskal-Wallis stratified rank sum trend test

data:  y , group:  x , strata:  b , trend:  as.numeric(group)
Z = -0.1624, df = 1, p-value = 0.871

> SKruskal.test(y ~ x | b, data = mydf, trend = 1:3)

        Kruskal-Wallis stratified rank sum trend test

data:  y , group:  x , strata:  b , trend:  1 2 3
Z = -0.1624, df = 1, p-value = 0.871

(The df=1 is a bit misleading in this case...)


-- 
   O__  ---- Peter Dalgaard             Øster Farimagsgade 5, Entr.B
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