[EMAIL PROTECTED] writes:
> } else {
> STATISTIC <- c(z = r / sqrt((4 * n + 10) / (9 * n*(n-1))))
> p <- pnorm(STATISTIC)
> if(exact && TIES)
> warning("Cannot compute exact p-value with ties")
> }
> }
> } else {
> // OMITTED
> }
> }
>
> if(is.null(PVAL)) # for "pearson" only, currently
> PVAL <- switch(alternative,
> "less" = p,
> "greater" = 1 - p,
> "two.sided" = 2 * min(p, 1 - p))
...
>
> Please look at the computation of the p-value for Kendalls tau. There is an
> assignment to "p" right above the warning. In the bottom of the function there
> is a comment that for the pearson case we have to use the modification and set
> PVAL.
>
> The problem is:
> * Either the comment is wrong because the modification should be done with
> kendall too, or
> * The variable PVAL has to be assigned in the kendall block.
>
> I hope this is clear so far.
I think it is the comment that is wrong. The calculation of
opposite-side one-sided and two-sided alternatives make OK sense when
the normal approximation of the test statistic is being used. It's
when you use a discrete distribution that you need to be careful.
(As brought up recently, the normal approximation itself is not too
hot in the tied case, but that's another matter.)
--
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
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
______________________________________________
R-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel
