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A Study of Dispersion Effect Identification using Levene-Type Transformations in Replicated Factorial Designs

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dc.contributor.advisor Umphrey, Gary
dc.contributor.author Cornelius, Haley
dc.date.accessioned 2017-05-02T19:10:18Z
dc.date.available 2018-04-21T05:00:24Z
dc.date.copyright 2017-04
dc.date.created 2017-04-21
dc.date.issued 2017-05-02
dc.identifier.uri http://hdl.handle.net/10214/10337
dc.description.abstract 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 result 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 in a 2^f factorial design will be performed and analyzed using an analysis of variance to identify dispersion effects. The use of these transformations, compared to a previous method, proves adequate with limitations. It is also of interest to determine how increasing the number of factors while holding the replication size and power level constant affects the detectable effect size. For a fixed power, the decrease in detectable effect size as the number of factors increases is quantified. en_US
dc.language.iso en en_US
dc.subject Replicated Factorial Designs en_US
dc.subject Levene's Test en_US
dc.subject Dispersion Effects en_US
dc.subject Levene Transformations en_US
dc.subject Absolute Deviation en_US
dc.subject Balanced Factorial Designs en_US
dc.subject Half-Normal Distribution en_US
dc.subject Folded-Normal Distribution en_US
dc.title A Study of Dispersion Effect Identification using Levene-Type Transformations in Replicated Factorial Designs en_US
dc.type Thesis en_US
dc.degree.programme Mathematics and Statistics en_US
dc.degree.name Master of Science en_US
dc.degree.department Department of Mathematics and Statistics en_US
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