ANTsR (version 0.3.3)

rftResults: RFT Statistical Results

Description

Returns RFT based statistical results for a single statistical image

Usage

rftResults(x, resels, fwhm, df, fieldType, RPVImg = NULL, k = 1, threshType = "pRFT", pval = 0.05, pp = 0.001, n = 1, statdir = NULL, verbose = FALSE)

Arguments

x

statistical field image of class antsImage

resels

resel values for the mask

fwhm

full width at half maxima

df

degrees of freedom expressed as df = c(degrees of interest, degrees of error)

fieldType

• T: T-field
• F: F-field
• X: Chi-square field'
• Z: Gaussian field

RPVImg

resels per voxel image

k

minimum desired cluster size (default = 1)

threshType

a numeric value to threshTypeold the statistical field or a character of the following methods:

• cRFT: computes a threshTypeold per expected cluster level probability
• pRFT: uses the mask and pval calculates the minimum statistical threshTypeold
• cFDR: uses an uncorrected threshTypeold at the alpha level and then computes and FDR threshTypeold based on cluster maxima
• pFDR: computes the fdr threshTypeold for the entire field of voxels

pval

the p-value for estimating the threshTypeold (default = .05)

pp

the primary (initial) p-value for threshTypeolding (only used for FDR methods; default = .001)

n

number of images in conjunction

statdir

directory where output is saved (if not specified images are not saved)

verbose

enables verbose output

Value

Outputs a statistical value to be used for threshTypeold a statistical field image

• SetStats: set-level statistics and number of clusters
• ClusterStats: cluster-level statistics and descriptors
• PeakStats: peak-level statistics and descriptor"
• LabeledClusters: image of labeled clusters
• threshTypeold: the threshTypeold used

Details

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.

References

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.

Examples

## Not run: 
# 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)
#                        
# ## End(Not run)