ANTsR (version 0.7.2.0)

rftPval: RFT p-values

Description

Calculates p-values of a statistical field using random field theory

Usage

rftPval(D, c, k, u, n, resels, df, fieldType)

Arguments

D

image dimensions

c

Threshold

k

spatial extent in resels (minimum cluster size in resels)

u

Number of clusters

n

number of statistical field in conjunction

resels

resel measurements of the search region

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

Value

The probability of obtaining the specified cluster

• Pcor: corrected p-value Pu: uncorrected p-value Ec: expected number of clusters ek: expected number of resels per cluster

Details

This function calculates p-values of a thresholded statistical field at various levels:

set-level rft.pval(D, c, k, u, n, resels, df, fieldType)

cluster-level rft.pval(D, 1, k, u, n, resels, df, fieldType)

peak-level rft.pval(D, 1, 0, u, n, resels, df, fieldType)

Where set-level refers to obtaining the set of clusters, cluster-level refers to a specific cluster, and peak-level refers to the maximum (or peak) of a single cluster.

References

Friston K.J., (1994) Assessing the Significance of Focal Activations Using Their Spatial Extent.

Friston K.J., (1996) Detecting Activations in PET and fMRI: Levels of Inference and Power.

Worlsey K.J., (1996) A Unified Statistical Approach for Determining Significant Signals in Images of Cerebral Activation.

See Also

rftResults, resels

Examples

# NOT RUN {
# using rftPval for hypothetical 3D t-statistical image
# assume resels have been calculated and df = c(dfi, dfe)

# peak RFT p-value (peak = the maximum of a specific cluster)
peakP <- rftPval(3, 1, 0, peak, 1, resels, df, fieldType = "T")$Pcor 

# cluster RFT p-value (u = the value the statistical field was threshold at
# and k = the size of the cluster in resels)
clusterP <- rftPval(3, 1, k, u, 1, resels, df, fieldType = "T")$Pcor 

# set RFT p-value 
setP <- rftPval(3, numberOfClusters, minimumClusterSize, u, 1, resels, df,
                fieldType = "T")$Pcor
# }