FDR_1D¶
- FDR_1D(varargin)¶
FDR_1D Performs statistical comparisons between 1D vectors using a False Discover Rate (FDR) approach
- Usage:
FDR_1D(group1, group2, <options>)
- Input:
group1: Numeric 1D vector x <trials> array representing the first group of data.
group2: Numeric 1D vector 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 an unpaired t-tests are used otherwise Default is true.
ploton: (Optional) Boolean indicating whether to plot the results. Default is true.
- Output:
sigbins: 1D vector indicating significant segments along the 1D dimension differing between group1 and group2.
p_adj: 1D Vector of adjusted p-values after multiple testing correction.
p_values: 1D vector of raw p-values.
- Example:
%Run FDR_1D() for demo data
- See also:
FDR_2D, fdr_bh
Copyright 2024 Michael J. Prerau Laboratory. - http://www.sleepEEG.org