Education Commons^™

Using Bayesian Multilevel Models To Control For Multiplicity Among Means, Michael J. Zweifel

College of Education and Human Sciences: Dissertations, Theses, and Student Research

It is well known that the Type I error rate will exceed α when multiple hypothesis tests are conducted simultaneously. This is known as Type I error inflation. The probability of committing a Type I error grows monotonically as the number as the number of hypothesis being tested increases. A class of methods, known as multiple comparison procedures, has been developed to combat this issue. However, in turn for maintaining the Type I error rate below α, multiple comparison procedures sacrifice power to correctly reject false hypotheses. The loss of power is exacerbated when variance heterogeneity is present.

In …