[MINC-users] mni.compute.FDR question

[Mishkin Derakhshan]

Hi,
I'm receiving what I think is an error (but might actually be a
result?) when I use the mni.compute.FDR function in R from the
mni.cortical.statistics package, but I'm not sure.

Here is my R code, and the warning messages:

library(mni.cortical.statistics)
gf <- mni.read.glim.file("input.glim",TRUE,FALSE,"csv")
dt <- mni.build.data.table(gf)
ms <- mni.mean.statistics(gf, 'y ~ group', vertex.table=dt)
summary(ms)
vs <- mni.vertex.statistics(gf, 'y ~ group', vertex.table=dt)
mni.write.vertex.stats(vs, "output.vertstats", mean.stats=ms, glim.matrix=gf)
q <- mni.compute.FDR(vs$tstatistic[,2], df=23, fdr=0.05)

Warning messages:
1: In max(r$ix[r$x == TRUE]) :
  no non-missing arguments to max; returning -Inf
2: In qt((sorted.p.values$x[max(r$ix[r$x == TRUE])])/2, df) :
  NAs introduced by coercion
3: In return(fdr.threshold, q) : multi-argument returns are deprecated


When I check the fdr threshold value it is NA. Does this mean that
there are no significant differences between my two groups, or is
there an error with my data? The reason I say this is because I ran
this exact code three time but with different groups:
1. CONTROLS VS SPMS - i get an fdr threshold
2. CONTROLS VS RRMS - i get NA
3. CONTROLS VS RENAMED-CONTROLS - I also get NA

which is how I reverse engineered my theory that there was no
significant difference. Of course I want to know if this is the case
for sure before I draw any conclusions about my data.

thanks,
mishkin