The Bonferroni correction is only one way to guard against the bias of repeated testing effects, but it is probably the most common method and it is definitely the most fun to say. I've come to consider it as critical to the accuracy of my analyses as selecting the correct type of analysis or entering the data accurately. Unfortunately adjustments for repeated testing of hypotheses, as a whole, remains something that is often overlooked by researchers and the consequences may very well be inaccurate results and misleading inferences. In this independence day blog, I'll discuss why the Bonferroni Correction should be as important as apple pie on the 4th of July.
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