[R] number of effective tests

[Charles C. Berry]

On Thu, 10 Jul 2008, Georg Ehret wrote:

> 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 what purpose?

If you are trying to perform a multiple comparisons adjustment, you might 
do better to skip this bit and go on to a resampling or permutational 
procedure. There is an enormous literature on this subject. One example:

@book{West:Youn:1993,
           author = {Westfall, Peter H. and Young, S. Stanley},
           title = {Resampling-based multiple testing: {E}xamples and
 			methods for $p$-value adjustment},
           year = {1993},
           pages = {340},
           ISBN = {0471557617},
           publisher = {John Wiley \& Sons},
           keywords = {Simultaneous inference; Bootstrap}
       }

HTH,

Chuck


> 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
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901