spm_P_RF: SPM: Returns the [un]corrected P value using unifed EC theory

In jpellman/spmR: Statistical Parametric Mapping in R

Description

spm_P_RF returns the probability of c or more clusters with more than k resels in volume process of R RESELS thresholded at u. All p values can be considered special cases:

spm_P_RF(1,0,z,df,STAT,1,n) = uncorrected p value spm_P_RF(1,0,z,df,STAT,R,n) = corrected p value (based on height z) spm_P_RF(1,k,u,df,STAT,R,n) = corrected p value (based on extent k at u) spm_P_RF(c,k,u,df,STAT,R,n) = corrected p value (based on number c at k and u) spm_P_RF(c,0,u,df,STAT,R,n) = omnibus p value (based on number c at u)

If n > 1 a conjunction probility over the n values of the statistic is returned

Usage

[P p Ec Ek] = spm_P_RF(c,k,z,df,STAT,R,n)

Arguments

c	- cluster number
k	- extent RESELS
z	- height minimum over n values
df	- [dfinterest dferror]
STAT	- Statistical field 'Z' - Gaussian field 'T' - T - field 'X' - Chi squared field 'F' - F - field
R	- RESEL Count defining search volume
n	- number of component SPMs in conjunction

Value

A list containing: P - corrected P value - P(C >= c | K >= k) p - uncorrected P value Ec - expected number of clusters (maxima) Ek - expected number of resels per cluster

References

Hasofer AM (1978) Upcrossings of random fields Suppl Adv Appl Prob 10:14-21

Friston KJ et al (1994) Assessing the Significance of Focal Activations Using Their Spatial Extent Human Brain Mapping 1:210-220

Worsley KJ et al (1996) A Unified Statistical Approach for Determining Significant Signals in Images of Cerebral Activation Human Brain Mapping 4:58-73

jpellman/spmR documentation built on May 19, 2019, 10:44 p.m.