Multiple Comparison Correction

Definition: Multiple comparison correction is a range of statistical procedures that allows one to take into account the fact that several statistical inferences are being performed simultaneously which increases the probability of observing a significant result just due to chance. An example would be a channel-wise comparison between two conditions or between two time points. When performing multiple statistical tests, the risk of increase in false positives known as Type 1 error is controlled by using multiple comparison correction procedures such as Bonferroni method, the False Discovery Rate (FDR) and Benjamini-Hochberg method.

Alternative definition:

Synonym: multiplicity problem

References: https://doi.org/10.1016/j.neuroimage.2006.06.047

Related terms: Bonferroni, FDR