FDR_2D

FDR_2D(varargin)

FDR_2D Performs statistical comparisons between 2D matrices using a False Discover Rate (FDR) approach

Usage:

FDR_2D(group1, group2, <options>)

Input:

• group1: Numeric <2D array dimensions> x <trials> array representing the first group of data.

• group2: Numeric <2D array dimensions> x <trials> array representing the second group of data.

• FDR: (Optional) False Discovery Rate (FDR) threshold for multiple testing correction. Default is 0.1.

• method: (Optional) ‘dependent’ will use the Benjamini & Yekutieli (2001) procedure, and ‘independent’ will use the Benjamini & Hochberg (1995) procedure that assumes data are independent or positively dependent. Default is ‘dependent’

• paired: (Optional) Boolean indicating whether the data in group1 and group2 are paired. Default is false.

• nonparam: (Optional) Boolean indicating whether to use nonparametric test.

  For nonparametric tests, a ranksum test is use for unpaired an a signrank test is used for paired. Paired and unpaired t-tests are used otherwise Default is true.

• ploton: (Optional) Boolean indicating whether to plot the results. Default is true.

Output:

• sigbins: 2D array indicating significant regions differing between group1 and group2.

• p_adj: 2D array of adjusted p-values after multiple testing correction.

• p_values: 2D array of raw p-values.

The FDR procedure is computed using a modified version of fdr_bh() authored by Groppe, D.M.

https://www.mathworks.com/matlabcentral/fileexchange/27418-fdr_bh

Example:

%Run FDR_2D() for demo data

See also:

FDR_1D, fdr_bh

Copyright 2024 Michael J. Prerau Laboratory. - http://www.sleepEEG.org

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