bonferroni_holm
Bonferroni-Holm (aka Holm-Bonferroni) determines whether a series of hypotheses are still significant controlling for family wise error rate (FWE) and subsequently controls for false discovery rate (FDR) The Bonferroni-Holm method corrects for multiple comparisons (hypothesis tests). It less conservative than the Bonferroni correction, but more powerful (so p-values are more likely to stay significant). This function accepts raw p values from 1 or more hypotheses and outputs the FWE-adjusted p-values, and a logical array indicating which p-values are still significant at alpha = 0.05 or other alpha, after correcting for FWE. See function code for instructions.
Cite As
E Zakreski (2026). bonferroni_holm (https://nl.mathworks.com/matlabcentral/fileexchange/69817-bonferroni_holm), MATLAB Central File Exchange. Retrieved .
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- AI and Statistics > Statistics and Machine Learning Toolbox > Probability Distributions and Hypothesis Tests > Hypothesis Tests >
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