[Rd] Spearman's rank correlation test

From: Petr Savicky <savicky_at_cs.cas.cz>
Date: Thu, 12 Feb 2009 13:33:33 +0100

Hi All:

help(cor.test) claims
For Spearman's test, p-values are computed using algorithm AS 89.

Algorithm AS 89 was introduced by the paper   D. J. Best & D. E. Roberts (1975), Algorithm AS 89: The Upper Tail   Probabilities of Spearman's rho. Applied Statistics, Vol. 24, No. 3, 377-379. Table 1(a) in this paper presents maximum absolute error |\Delta_m|, of the approximation for all possible values of the statistic S for samples sizes n = 7, 9, 11, 13. The presented errors are

n |\Delta_m|

```   7  0.0046
9  0.0011
11  0.0006
13  0.0005

```

Due to the problem explained in detail including a patch at   https://stat.ethz.ch/pipermail/r-devel/2009-January/051936.html the error of R implementation of Spearman's rank correlation test is larger than the above bounds for the sample size n = 11 and some of the values of S, which correspond to positive correlation.

For example, for n = 11 and S = 90, we have   x <- 1:11
y <- c(6:1, 7, 11:8)
out <- cor.test(x, y, method="spearman", alternative="greater")   out\$statistic # 90
out\$p.value # 0.02921104
while the correct p-value is 0.03044548, so the absolute difference is 0.00123444. This is larger than the absolute error 0.0006 guaranteed for AS 89. In my opinion, this means that the claim from help(cor.test) cited above is not correct.

To see the error of AS 89 in the example above, one can use   cor.test(x, -y, method="spearman", alternative="less")\$p.value # 0.03036413 since on the side of negative correlation, R calls AS 89 correctly. So, for the x, y above, correctly called AS 89 has absolute error 0.00008135.

There is a package pspearman currently included to CRAN, which provides a correction of the problem without the need to modify R base.

Petr.

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Thu 12 Feb 2009 - 11:49:48 GMT

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