Quantitative Psychology 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 …

A Comparison Of Alternative Bias-Corrections In The Bias-Corrected Bootstrap Test Of Mediation, Donna Chen

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

Although the bias-corrected (BC) bootstrap is an oft recommended method for obtaining more powerful confidence intervals in mediation analysis, it has also been found to have elevated Type I error rates in conditions with small sample sizes. Given that the BC bootstrap is used most often in studies with low power due to small sample size, the focus of this study is to consider alternative measures of bias that will reduce the elevated Type I error rate without reducing power. The alternatives examined fall under two categories: bias correction and transformation. Although the bias correction methods did not significantly decrease …