# family wise error rate

### What is Family-wise Error Rate?

December 8th, 2023 by

In statistical practice, there are many situations where best practices are clear. There are many, though, where they aren’t. The granddaddy of these practices is adjusting p-values when you make multiple comparisons. There are good reasons to do it and good reasons not to. It depends on the situation.

At the heart of the issue is a concept called Family-wise Error Rate (FWER). FWER is the probability that

### Member Training: Adjustments for Multiple Testing: When and How to Handle Multiplicity

May 3rd, 2018 by
A research study rarely involves just one single statistical test. And multiple testing can result in more statistically significant findings just by chance.

After all, with the typical Type I error rate of 5% used in most tests, we are allowing ourselves to “get lucky” 1 in 20 times for each test.  When you figure out the probability of Type I error across all the tests, that probability skyrockets.
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### Member Training: Multiple Comparisons

June 1st, 2014 by

Whenever you run multiple statistical tests on the same set of data, you run into the problem of the Familywise Error Rate. What this means is that the true probability

of a type 1 error somewhere in the family of tests you’re running is actually higher than the alpha=.05 you’re using for any given test.

This is a complicated and controversial issue in statistics — even statisticians argue about whether it’s a problem, when it’s a problem, and what to do about it.

In this webinar, we’ll talk about the meaning and consequences of these issues so you can make informed decisions in your data analysis.

We’ll also go through possible solutions, including post-hoc tests and the false discovery rate.

Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

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