Dear R community,
I am using 6 variables to test for an effect (by linear regression).
These 6 variables are strongly correlated among each other and I would like
to find out the number of independent test that I perform in this
calcuation. For this I calculated a matrix of correlation coefficients
between the variables (see below). But to find the rank of the table in R is
not the right approach... What else could I do to find the effective number
of independent tests?
Any suggestion would be very welcome!
Thanking you and with my best regards, Georg.
> for (a in 1:6){
+ for (b in 1:6){
+
r[a,b]<-summary(lm(unlist(d[a])~unlist(d[b])),na.action="na.exclude")$adj.r.squared
+ }
+ }
>
> r
SR SU ST DR DU DT
SR 1.0000000 0.9636642 0.9554952 0.2975892 0.3211303 0.3314694
SU 0.9636642 1.0000000 0.9101678 0.3324979 0.3331389 0.3323826
ST 0.9554952 0.9101678 1.0000000 0.2756876 0.3031676 0.3501157
DR 0.2975892 0.3324979 0.2756876 1.0000000 0.9981733 0.9674843
DU 0.3211303 0.3331389 0.3031676 0.9981733 1.0000000 0.9977780
DT 0.3314694 0.3323826 0.3501157 0.9674843 0.9977780 1.0000000
*************************
Georg Ehret
Johns Hopkins University
Baltimore, US
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