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dc.contributor.authorHemmer, Michael Toshiro
dc.description.abstractNonparametric tests have served as robust alternatives to traditional statistical tests with rigid underlying assumptions. If a researcher expects the treatment effects to follow an umbrella alternative, then the test developed in this research will be applicable in the Balanced Incomplete Block Design (Hemmer’s test). It is hypothesized that Hemmer’s test will prove to be more powerful than the Durbin test when the umbrella alternative is true. A mixed design consisting of a Balanced Incomplete Block Design and a Randomized Complete Block Design will also be considered, where two additional test statistics are developed for the umbrella alternative. Monte Carlo simulation studies were conducted using SAS to estimate powers. Various underlying distributions were used with 3, 4, and 5 treatments, and a variety of peaks and mean parameter values. For the mixed design, different ratios of complete to incomplete blocks were considered. Recommendations are given.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.titleNonparametric Test for the Umbrella Alternative in a Randomized Complete Block and Balanced Incomplete Block Mixed Designen_US
dc.typeThesisen_US
dc.date.accessioned2017-10-24T19:59:04Z
dc.date.available2017-10-24T19:59:04Z
dc.date.issued2012
dc.identifier.urihttps://hdl.handle.net/10365/26696
dc.subject.lcshNonparametric statistics.en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeScience and Mathematicsen_US
ndsu.departmentStatisticsen_US
ndsu.programStatisticsen_US
ndsu.advisorMagel, Rhonda


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