Threshold.FDR: False Discovery Rate (FDR) Threshold

In AnalyzeFMRI: Functions for Analysis of fMRI Datasets Stored in the ANALYZE or NIFTI Format

Description

Calculates the False Discovery Rate (FDR) threshold for a given vector of statistic values.

Usage

Threshold.FDR(x, q, cV.type = 2, type = c("Normal", "t", "F"), df1 = NULL, df2 = NULL)

Arguments

x	A vector of test statistic values.
q	The desired False Discovery Rate threshold.
cV.type	A flag that specifies the assumptions about the joint distribution of p-values. Choose cV.type = 2 for fMRI data (see Genovese et al (2001)
type	The distribution of the statistic values. Either "Normal", "t" or "F".
df1	The degrees of freedom of the t-distribution or the first degrees of freedom parameter for the F distribution.
df2	The second degrees of freedom parameter for the F distribution.

Value

Returns the FDR threshold.

Author(s)

J. L. Marchini

References

Genovese et al. (2001) Thresholding of Statistical Maps in Functional NeuroImaging Using the False Discovery Rate.

Examples

x <- c(rnorm(1000), rnorm(100, mean = 3))
Threshold.FDR(x = x, q = 0.20, cV.type = 2) 

Example output

Loading required package: R.matlab
R.matlab v3.6.2 (2018-09-26) successfully loaded. See ?R.matlab for help.

Attaching package: ‘R.matlab’

The following objects are masked from ‘package:base’:

    getOption, isOpen

Loading required package: fastICA
Loading required package: tcltk
Loading required package: tkrplot
Warning messages:
1: no DISPLAY variable so Tk is not available 
2: loading Rplot failed 
[1] 3.075529

AnalyzeFMRI documentation built on Oct. 5, 2021, 5:06 p.m.