y4_Threshold.FDR: False Discovery Rate (FDR) Threshold

In MixfMRI: Mixture fMRI Clustering Analysis

False Discovery Rate (FDR) Threshold

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.

Details

Note: This function is directly copied from "AnalyzeFMRI".

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) 

MixfMRI documentation built on Sept. 8, 2023, 5:06 p.m.