Comparisons of Improvement-Over-Chance Effect Sizes for Two Groups Under Variance Heterogeneity and Prior Probabilities Metadata

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Title

  • Main Title Comparisons of Improvement-Over-Chance Effect Sizes for Two Groups Under Variance Heterogeneity and Prior Probabilities

Creator

  • Author: Alexander, Erika D.
    Creator Type: Personal

Contributor

  • Chair: Henson, Robin K.
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Young, Jon I.
    Contributor Type: Personal
  • Committee Member: Schumacker, Randall E.
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas

Date

  • Creation: 2003-05
  • Digitized: 2003-05-13

Language

  • English

Description

  • Content Description: The distributional properties of improvement-over-chance, I, effect sizes derived from linear and quadratic predictive discriminant analysis (PDA) and from logistic regression analysis (LRA) for the two-group univariate classification were examined. Data were generated under varying levels of four data conditions: population separation, variance pattern, sample size, and prior probabilities. None of the indices provided acceptable estimates of effect for all the conditions examined. There were only a small number of conditions under which both accuracy and precision were acceptable. The results indicate that the decision of which method to choose is primarily determined by variance pattern and prior probabilities. Under variance homogeneity, any of the methods may be recommended. However, LRA is recommended when priors are equal or extreme and linear PDA is recommended when priors are moderate. Under variance heterogeneity, selecting a recommended method is more complex. In many cases, more than one method could be used appropriately.

Subject

  • Library of Congress Subject Headings: Discriminant analysis.
  • Library of Congress Subject Headings: Logistic regression analysis.
  • Keyword: Index
  • Keyword: effect sizes
  • Keyword: predictive discriminant analysis
  • Keyword: logistic regression
  • Keyword: simulation

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights License: copyright
  • Rights Holder: Alexander, Erika D.
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • OCLC: 53153177
  • Archival Resource Key: ark:/67531/metadc4242

Degree

  • Degree Name: Doctor of Philosophy
  • Degree Level: Doctoral
  • Degree Discipline: Educational Research
  • Academic Department: College of Education
  • Degree Grantor: University of North Texas

Note

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