MSc Statistics Defence: A Study of Dispersion Effect Indentification Using Levene-Type Transformations in R Replicated Factorial Designs

CANDIDATE:   HALEY CORNELIUS

Interest in the analysis of dispersion effects has become increasingly popular and many methods for identifying such effects in factorial designs have been proposed; however, many methods for replicated designs typically results in a loss in degrees of freedom.  Levene-type transformations were introduced as a means to transform the response variable such that each observation is now a measure of dispersion.  In this thesis, six Levene-type transformations of the response variable will be performed and analyzed using an Analysis of Variance to identify dispersion effects.  This proposed simplified method, compared to a previous method, proves adequate with limitations.  Given this adequacy, it is then of interest to determine how increasing the number of factors while holding replication size and power level constant affects the detectible effect size.  It was determine that there is a significant decrease in the detectible effect size as the number of factors increases.