Comparing Three Approaches for Handling a Fourth Level of Nesting Structure in Cluster-Randomized Trials Metadata

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Title

  • Main Title Comparing Three Approaches for Handling a Fourth Level of Nesting Structure in Cluster-Randomized Trials

Creator

  • Author: Glaman, Ryan
    Creator Type: Personal

Contributor

  • Chair: Henson, Robin K.
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Boesch, Miriam C.
    Contributor Type: Personal
  • Committee Member: Eddy, Colleen M.
    Contributor Type: Personal
  • Committee Member: Hull, Darrell M.
    Contributor Type: Personal

Publisher

  • Name: University of North Texas
    Place of Publication: Denton, Texas
    Additional Info: www.unt.edu

Date

  • Creation: 2017-08

Language

  • English

Description

  • Content Description: This study compared 3 approaches for handling a fourth level of nesting structure when analyzing data from a cluster-randomized trial (CRT). CRTs can include 3 levels of nesting: repeated measures, individual, and cluster levels. However, above the cluster level, there may sometimes be an additional potentially important fourth level of nesting (e.g., schools, districts, etc., depending on the design) that is typically ignored in CRT data analysis. The current study examined the impact of ignoring this fourth level, accounting for it using a model-based approach, and accounting it using a design-based approach on parameter and standard error (SE) estimates. Several fixed effect and random effect variance parameters and SEs were biased across all 3 models. In the 4-level model, most SE biases decreased as the number of level 3 clusters increased and as the number of level 4 clusters decreased. Also, random effect variance biases decreased as the number of level 3 clusters increased. In the 3-level and complex models, SEs became more biased as the weight level 4 carried increased (i.e., larger intraclass correlation, more clusters at that level). The current results suggest that if a meaningful fourth level of nesting exists, future researchers should account for it using design-based approach; the model-based approach is not recommended. If the fourth level is not practically important, researchers may ignore it altogether.
  • Physical Description: v, 41 pages

Subject

  • Keyword: multilevel modeling
  • Keyword: hierarchical linear modeling
  • Keyword: cluster-randomized trial
  • Keyword: latent growth curve modeling
  • Keyword: nested data
  • Keyword: Education, Educational Psychology
  • Keyword: Statistics
  • Library of Congress Subject Headings: Multilevel models (Statistics)
  • Library of Congress Subject Headings: Cluster analysis.
  • Library of Congress Subject Headings: Statistics -- Methodology.

Collection

  • Name: UNT Theses and Dissertations
    Code: UNTETD

Institution

  • Name: UNT Libraries
    Code: UNT

Rights

  • Rights Access: public
  • Rights Holder: Glaman, Ryan
  • Rights License: copyright
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights Reserved.

Resource Type

  • Thesis or Dissertation

Format

  • Text

Identifier

  • Accession or Local Control No: submission_807
  • Archival Resource Key: ark:/67531/metadc1011881

Degree

  • Degree Name: Doctor of Philosophy
  • Degree Level: Doctoral
  • Academic Department: Department of Educational Psychology
  • College: College of Education
  • Degree Discipline: Educational Psychology
  • Degree Publication Type: disse
  • Degree Grantor: University of North Texas

Note

  • Embargo Note: The work will be published after approval.
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