Date of Award
5-2017
Degree Type
Report
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
Committee Chair(s)
John R. Stevens
Committee
John R. Stevens
Committee
Yan Sun
Committee
Chris Corcoran
Abstract
A community ecologist provided a motivating data set involving a certain animal species with two behavior groups, along with a pairwise genetic distance matrix among individuals. Many community ecologists have analyzed similar data sets with a method known as the Hopkins method, testing for an association between the subject-level covariate (behavior group) and the pairwise distance. This community ecologist wanted to know if they used the Hopkins method, would their results be meaningful? Their question inspired this thesis work, where a different data set was used for confidentiality reasons. Multiple methods (Hopkins method, ADONIS, ANOSIM, and Distance Regression) were used to analyze the distance matrix for association with a binary covariate of interest. To compare the performance of the Hopkins method with the performance of the remaining, more established methods, a simulation was run. The results of the simulation indicate that ADONIS, ANOSIM, and distance regression would all be preferable to the Hopkins method.
Recommended Citation
Stone, Rachael, "A Comparison of Statistical Methods RElating Pairwise Distance to a Binary Subject-Level Covariate" (2017). All Graduate Plan B and other Reports, Spring 1920 to Spring 2023. 931.
https://digitalcommons.usu.edu/gradreports/931
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