On Aug 18, 2010, at 11:55 AM, Cedric Laczny wrote:
> I was able to trace down the unexpected behavior to the following line
> SIGMA <- sqrt((n.x * n.y/12) * ((n.x + n.y + 1) -
>sum(NTIES^3 - NTIES)/((n.x + n.y) * (n.x + n.y -
> 1
> My calculations of the Z-s
I was able to trace down the unexpected behavior to the following line
SIGMA <- sqrt((n.x * n.y/12) * ((n.x + n.y + 1) -
sum(NTIES^3 - NTIES)/((n.x + n.y) * (n.x + n.y -
1
My calculations of the Z-score for the normal approximation where based on
using the s
Thanks for the hint.
I tested this generic example and had the same behavior also in a special
example, that can be found below. This example does not involve continuity
correction but exibits the same "unexpected" behavior:
GDS_example = function()
{
print("---> GDS EXAMPLE <---", quote
After fixing the parentheses in your code so it does run, it seems that the
difference is that wilcox.test defaults to using a continuity correction and
your manual calculation does not. Use wilcox.test(big1, big2, correct=FALSE).
-thomas
On Tue, 17 Aug 2010, Cedric Laczny wrote:
Hi,
Hi,
I became a little bit confused when working with the Wilcoxon test in R.
As far as I understood, there are mainly two versions:
1) wilcox.test{stats}, which is the default and an approximation, especially,
when ties are involved
2) wilcox_test{coin}, which does calculate the distribution _exa
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