rftResults.RdReturns RFT based statistical results for a single statistical image
rftResults(
x,
resels,
fwhm,
df,
fieldType,
RPVImg = NULL,
k = 1,
threshType = "pRFT",
pval = 0.05,
pp = 0.001,
n = 1,
statdir = NULL,
verbose = FALSE
)statistical field image of class antsImage
resel values for the mask
full width at half maxima
degrees of freedom expressed as df = c(degrees of interest, degrees of error)
T-field
F-field
Chi-square field'
Gaussian field
resels per voxel image
minimum desired cluster size (default = 1)
a numeric value to threshTypeold the statistical field or a character of the following methods:
computes a threshTypeold per expected cluster level probability
uses the mask and pval calculates the minimum statistical threshTypeold
uses an uncorrected threshTypeold at the alpha level and then computes and FDR threshTypeold based on cluster maxima
computes the fdr threshTypeold for the entire field of voxels
the p-value for estimating the threshTypeold (default = .05)
the primary (initial) p-value for threshTypeolding (only used for FDR methods; default = .001)
number of images in conjunction
directory where output is saved (if not specified images are not saved)
enables verbose output
Outputs a statistical value to be used for threshTypeold a statistical field image
set-level statistics and number of clusters
cluster-level statistics and descriptors
peak-level statistics and descriptor"
image of labeled clusters
the threshTypeold used
rftPval is used to compute all family-wise error (FWE) corrected
statistics while p.adjust is used to compute all false-discovery rate
based statistics. All statistics herein involve implementation of random
field theory (RFT) to some extent.
Both cluster-level and peak-level statistics are described by the
uncorrected
p-value along with the FDR and FWE corrected p-values for each cluster.
Peak-level statistics are described by the maximum statistical value in each
cluster and the comparable Z statistic. The ClusterStats table also contains
coordinates for each cluster and the number of voxels therein. By default
threshType = "pRFT" and pval=.05. Alternatively, the user may use a
specific numeric value for threshTypeolding the statistical field.
statFieldThresh more fully describes using appropriate threshTypeolds
for statistical fields and how pp plays a role in FDR
threshTypeolding.
Chumbley J., (2010) Topological FDR for neuroimaging
Friston K.J., (1996) Detecting Activations in PET and fMRI: Levels of Inference and Power
Worsley K.J., (1992) A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain.
if (FALSE) { # \dontrun{
mnit1 <- antsImageRead(getANTsRData("mni"))
mask <- getMask(mnit1)
ilist <- list()
for (i in 1:10) {
ilist <- lappend(ilist, antsImageClone(mnit1) * rnorm(1))
}
response <- rnorm(10)
imat <- imageListToMatrix(ilist, mask)
residuals <- matrix(nrow = nrow(imat), ncol = ncol(imat))
tvals <- matrix(nrow = nrow(imat), ncol = ncol(imat))
for (i in 1:ncol(imat)) {
fit <- lm(response ~ imat[, i])
tvals <- coefficients(fit)[2]
residuals[, i] <- residuals(fit)
}
myfwhm <- estSmooth(residuals, mask, fit$df.residual)
res <- resels(mask, myfwhm$fwhm)
timg <- makeImage(mask, tvals)
# threshold to create peak values with p-value of .05 (default)
results1 <- rftResults(timg, res, myfwhm$fwhm, df,
fieldType = "T",
threshType = "pRFT", pval = .05
)
# threshold to create clusters with p-value of .05
results2 <- rftResults(timg, res, myfwhm$fwhm, df,
fieldType = "T",
threshType = "cRFT", pval = .05
)
# initial threshold at p-value of .001 followed by peak FDR threshTypeold at
# p-value of .05
results3 <- rftResults(timg, res, myfwhm$fwhm, df,
fieldType = "T",
threshType = "pFDR", pval = .05, pp = .01
)
# initial threshold at p-value of .001 followed by cluster FDR threshold at
# p-value of .05
results4 <- rftResults(timg, res, myfwhm$fwhm, df,
fieldType = "T",
threshType = "cFDR", pval = .05, pp = .01
)
# correcting for non-isotropic
results5 <- rftResults(timg, res, myfwhm$fwhm, df,
fieldType = "T",
fwhm$RPVImg
)
} # }