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Title page for ETD etd-09212018-133542


Type of Document Master's Thesis
Author O'Keefe, Patrick Gerald
Author's Email Address patrick.okeefe@vanderbilt.edu
URN etd-09212018-133542
Title An Application of Univariate Bootstrapping to DeFries-Fulker Regression Models
Degree Master of Science
Department Psychology
Advisory Committee
Advisor Name Title
Joseph Lee Rodgers Committee Chair
Andrew Tomarkin Committee Member
Kristopher Preacher Committee Member
Keywords
  • bootstrapping
  • univariate bootstrapping
  • DeFries-Fulker
  • Behavioral Genetics
Date of Defense 2018-07-26
Availability unrestricted
Abstract
The univariate bootstrap is a relatively recently developed version of the bootstrap (Lee & Rodgers, 1998). Currently, research on the univariate bootstrap has largely focused on individual, bivariate correlations. DeFries-Fulker (DF) analysis is a regression model used to estimate parameters in behavioral genetic models (DeFries & Fulker, 1985). It is appealing for its simplicity; however, it violates certain regression assumptions such as homogeneity of variance and independence of errors that make calculation of standard errors and confidence intervals problematic. Methods have been developed to account for these issues (Kohler & Rodgers, 2001), however the univariate bootstrap represents a unique means of doing so that is presaged by suggestions from previous DF research (e.g., Cherny, Cardon, Fulker, & DeFries, 1992). DF analysis also presents an ideal area for application of univariate bootstrapping in that DF analysis primarily relies on a bivariate (intraclass) correlation, however it provides a convenient stepping off point for potential future applications of univariate bootstrapping to more complex models.
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