View in EDS HTML Full Text PDF Full Text

A methodological review of structural equation modelling in higher education research.

Saved in:
Bibliographic Details
Title: A methodological review of structural equation modelling in higher education research.
Authors: Green, Teegan (AUTHOR)
Source: Studies in Higher Education. Dec2016, Vol. 41 Issue 12, p2125-2155. 31p. 6 Charts, 2 Graphs.
Subjects: Structural equation modeling, Multivariate analysis, Statistics on social sciences, Common method variance, Higher education
Abstract: Despite increases in the number of articles published in higher education journals using structural equation modelling (SEM), research addressing their statistical sufficiency, methodological appropriateness and quantitative rigour is sparse. In response, this article provides a census of all covariance-based SEM articles published up until 2013 (N = 143) across eight leading higher education journals: The Review of Higher Education, Journal of Higher Education, Research in Higher Education, Higher Education, Studies in Higher Education, Assessment & Evaluation in Higher Education, Higher Education Research & Development and Journal of College Student Development. Several areas for improvement are found regarding the statistical application of SEM in higher education research. Recommendations are to focus on: building theoretically supported models, data screening, missing data, estimation methods, sample size and power, fit indices, validity and reliability and the testing of alternative models. Best-practice statistical guidelines for higher education researchers wishing to apply SEM to their research are provided. [ABSTRACT FROM AUTHOR]
Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 118972040
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A methodological review of structural equation modelling in higher education research.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Green%2C+Teegan%22">Green, Teegan</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Studies+in+Higher+Education%22">Studies in Higher Education</searchLink>. Dec2016, Vol. 41 Issue 12, p2125-2155. 31p. 6 Charts, 2 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics+on+social+sciences%22">Statistics on social sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Common+method+variance%22">Common method variance</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Despite increases in the number of articles published in higher education journals using structural equation modelling (SEM), research addressing their statistical sufficiency, methodological appropriateness and quantitative rigour is sparse. In response, this article provides a census of all covariance-based SEM articles published up until 2013 (N = 143) across eight leading higher education journals: The Review of Higher Education, Journal of Higher Education, Research in Higher Education, Higher Education, Studies in Higher Education, Assessment & Evaluation in Higher Education, Higher Education Research & Development and Journal of College Student Development. Several areas for improvement are found regarding the statistical application of SEM in higher education research. Recommendations are to focus on: building theoretically supported models, data screening, missing data, estimation methods, sample size and power, fit indices, validity and reliability and the testing of alternative models. Best-practice statistical guidelines for higher education researchers wishing to apply SEM to their research are provided. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Studies in Higher Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=118972040
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/03075079.2015.1021670
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 31
        StartPage: 2125
    Subjects:
      – SubjectFull: Structural equation modeling
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Statistics on social sciences
        Type: general
      – SubjectFull: Common method variance
        Type: general
      – SubjectFull: Higher education
        Type: general
    Titles:
      – TitleFull: A methodological review of structural equation modelling in higher education research.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Green, Teegan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2016
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-print
              Value: 03075079
          Numbering:
            – Type: volume
              Value: 41
            – Type: issue
              Value: 12
          Titles:
            – TitleFull: Studies in Higher Education
              Type: main
ResultId 1