[R] multiple-test correlation

[Robert A LaBudde]

At 07:35 AM 2/14/2010, Manuel Jesús López Rodríguez wrote:
>Dear all,
>I am trying to study the correlation between one 
>"independent" variable ("V1") and several others 
>dependent among them ("V2","V3","V4" and "V5"). 
>For doing so, I would like to analyze my data by 
>multiple-test (applying the Bonferroni´s 
>correction or other similar), but I do not find 
>the proper command in R. What I want to do is to 
>calculate Kendall´s correlation between "V1" and 
>the others variables (i.e. "V1" vs "V2", "V1" vs 
>"V3", etc.) and to correct the p values by 
>Bonferroni or other. I have found 
>"outlier.test", but I do not know if this is 
>what I need (also, I would prefer to use a less 
>conservative method than Bonferroni´s, if possible).
>Thank you very much in advance!

One approach might be to first test for any 
correlations via a likelihood ratio test:

Ho: P = I       (no correlations) or covariances are diagonal
T = -a ln V     ~ chi-square [p(p-1)/2]

where

V = det(R)
a = N -1 - (2 p +5)/6   N = # data
p = # variables

Reject Ho if T > X^2 (alpha, p(p-1)/2)

Then do the pairwise tests without familywise 
error control. I.e., this is similar to doing the 
F test in ANOVA before doing LSD testing.

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Robert A. LaBudde, PhD, PAS, Dpl. ACAFS  e-mail: ral at lcfltd.com
Least Cost Formulations, Ltd.            URL: http://lcfltd.com/
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