[R] pairwise.var.test

[Jim Lemon]

Hi Thomas,
I have assumed the format of your p-value matrix. This may require
some adjustment.

  A          B          C         D           E           F
A 1          0.7464     0.0187    0.0865      0.0122      0.4693
B 0.7464     1          0.0358    0.1502      0.0173      0.3240
C 0.0187     0.0358     1         0.5131      0.7185      0.0050
D 0.0865     0.1502     0.5131    1           0.3240      0.0173
E 0.0122     0.0173     0.7185    0.3240      1           0.0029
F 0.4693     0.3240     0.0050    0.0173      0.0029      1

pvar.mat<-as.matrix(read.table(text=
 "1          0.7464     0.0187    0.0865      0.0122      0.4693
 0.7464     1          0.0358    0.1502      0.0173      0.3240
 0.0187     0.0358     1         0.5131      0.7185      0.0050
 0.0865     0.1502     0.5131    1           0.3240      0.0173
 0.0122     0.0173     0.7185    0.3240      1           0.0029
 0.4693     0.3240     0.0050    0.0173      0.0029      1",
 stringsAsFactors=FALSE))
rownames(pvar.mat)<-colnames(pvar.mat)<-LETTERS[1:6]
pvar.col<-matrix(NA,nrow=6,ncol=6)
pvar.col[pvar.mat < 1]<-"red"
pvar.col[pvar.mat < 0.05]<-"orange"
pvar.col[pvar.mat < 0.01]<-"green"
library(plotrix)
par(mar=c(6,4,4,2))
color2D.matplot(pvar.mat,cellcolors=pvar.col,
 main="P-values for matrix",axes=FALSE)
axis(1,at=seq(0.5,5.5,by=1),labels=LETTERS[1:6])
axis(2,at=seq(0.5,5.5,by=1),labels=rev(LETTERS[1:6]))
color.legend(0,-1.3,2.5,-0.7,c("NA","NS","<0.05","<0.01"),
 rect.col=c(NA,"red","orange","green"))

Jim

On Mon, Oct 31, 2022 at 6:34 AM Thomas Subia via R-help
<r-help using r-project.org> wrote:
>
> Colleagues,
>
> The RVAideMemoire package has a pairwise variance test which one can use to identify variance differences between group levels.
>
> Using the example from this package, pairwise.var.test(InsectSprays$count,InsectSprays$spray), we get this output:
>
>     Pairwise comparisons using F tests to compare two variances
>
> data:  InsectSprays$count and InsectSprays$spray
>
>    A              B             C             D            E
> B 0.7464     -               -              -              -
> C 0.0187     0.0358     -      -       -
> D 0.0865     0.1502     0.5131     -             -
> E 0.0122     0.0173     0.7185     0.3240    -
> F 0.4693     0.3240     0.0050     0.0173     0.0029
>
> P value adjustment method: fdr
>
> Is there a way to graph the pairwise variance differences so that users can easily identify the statistically significant variance differences between group levels?
>
> I can do this using Minitab but I'd prefer using R for this.
>
> Thomas Subia
>
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