Q: 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.
http://www.bic.mni.mcgill.ca/pipermail/minc-users/2008-November/002265.html

A:Yup, that’s exactly what it means: no results at that FDR - see min(q $q) for the best possible FDR threshold in that particular dataset.