Permutation tests for mixed paired and two-sample designs
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Emily Nance Johnson (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Scott Richter
Abstract: In this thesis we propose permutation tests of previously developed statistics for the case of mixed paired and two-sample data. We also explore the different weighting schemes of previous tests to understand the strengths and weaknesses of each test. We compare the power and Type I error of our new tests and those previously developed through a simulation. Rank based statistics generally performed as well as if not better than parametric statistics for all distributions.
Permutation tests for mixed paired and two-sample designs
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Created on 8/1/2018
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Additional Information
- Publication
- Thesis
- Language: English
- Date: 2018
- Keywords
- Missing data, Nonparametric, Permutation
- Subjects
- Permutations
- Nonparametric statistics
- Missing observations (Statistics)