Variability in Meta-Analytic Effect Sizes and Meta-Analysis Outcomes as a Function of Measurement Procedure: A Simulation Study.

Meta-analysis is an important tool for identifying best practices. Critical to metaanalysis is the presumption that effect sizes based upon different measurement procedures are directly comparable. Recent theoretical work has challenged this notion, showing that two validity-invariance conditions mu...

Full description

Bibliographic Details
Published in:Best Practice in Mental Health Vol. 4; no. 2; pp. 80 - 99
Main Authors: Nugent, William R., Ely, Gretchen E.
Format: Article
Published: Lyceum Books, Inc. Summer 2008
Subjects:
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=510838187&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 510838187
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        1553555X
        14GH
      jtl: Best Practice in Mental Health
      issn: 1553555X
      maglogo: N
    pubinfo:
      dt: Summer 2008
      vid: 4
      iid: 2
      pid: 21168
      pub: Lyceum Books, Inc.
    artinfo:
      ui: 510838187
      ppf: 80
      ppct: 19
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
              size: 1.1MB
      tig:
        atl: Variability in Meta-Analytic Effect Sizes and Meta-Analysis Outcomes as a Function of Measurement Procedure: A Simulation Study.
      aug:
        au:
          Nugent, William R.
          Ely, Gretchen E.
      su:
        Psychological techniques
        Psychology -- Statistical methods
        Effect sizes (Statistics)
        Meta-analysis
      sug:
        subj:
          Psychological techniques
          Psychology -- Statistical methods
          Effect sizes (Statistics)
          Meta-analysis
      ab: Meta-analysis is an important tool for identifying best practices. Critical to metaanalysis is the presumption that effect sizes based upon different measurement procedures are directly comparable. Recent theoretical work has challenged this notion, showing that two validity-invariance conditions must hold in order for effect sizes based upon the different measures to be directly comparable. However, no research has been done investigating how much of a practical difference violations of these invariance conditions make in either effect-size variability or in the outcomes of a meta-analysis. This article reports the results of a simulation study of the practical effects that violations of one of these invariance conditions have on the differences in standardized mean difference effect sizes for a given between-population comparison, on the variability in correlation effect sizes for a given relationship in a given population, and on the results of a meta-analysis. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N