Physical Sciences and Mathematics Commons^™

Development Of Efficient Simultaneous Confidence Bounds For Linear Mixed Models With Applications In Alcohol Research, Emmanuel Joseph Sequeira

Open Access Theses & Dissertations

Multiplicity corrections are necessary to ensure the accuracy of conclusions made in studies that carry out multiple inferences simultaneously. This Thesis uses the methodology derived by Hunter and Worsley to obtain improved simultaneous confidence bounds (SCBs) that are less conservative than the highly used Bonferroni SCBs, for studies using linear mixed modeling. Empirical coverage rates were obtained for data that was generated using simulations, to compare the accuracy of the Hunter-Worsley SCBs with that of the Bonferroni SCBs. The bounds were also applied to data in the field of alcohol research, where comparisons were made to determine the moderating effect …