mcpCorrect: Calculate Multiple Comparison Corrections

In arf3DS4: Activated Region Fitting, fMRI data analysis (3D).

Description

mcpCorrect calculates three types of multiple comparison corrections: 'uncorrected', 'bonferroni', and 'False Discovery Rate (FDR)'. mcpCorrect assumes the data are t-values.

Usage

mcpCorrect(fmridata, type = c("uncorrected", "bonferroni", "FDR"), 
 alpha = 0.05, q = 0.05, cv = 1, df = 100, sig.steps = 1, adj.n = T)

Arguments

fmridata	An object of class ".fmri.data" (see fmri.data).
type	Type of correction ('uncorrected', 'bonferroni', 'FDR')
alpha	Nominal alpha level.
q	q parameter for FDR.
cv	Cv parameter for FDR.
df	Degrees of freedom of the t-values.
sig.steps	Number of steps to divide p-values in (for visualization).
adj.n	Use only brain voxels when correcting?

Value

Returns two object of class "fmri.data", one with suprathreshold voxels masked, one with only sigificant voxels used for overlay images.

Author(s)

Wouter D. Weeda - [e-mail]

See Also

fmri.data

arf3DS4 documentation built on May 2, 2019, 5:16 p.m.