SEM being more effective than multiple regression in parsimonious model testing for management development research

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130 Citations (Scopus)

Abstract

Aims to commend SEM (structural equation modeling) that excels beyond multiple regression, which is a popular statistical technique to test the relationships of independent and dependent variables, in expanding the explanatory ability and statistical efficiency for parsimonious model testing with a single comprehensive method. SEM is employed to find the real "best fitting" model. This article also presents an incremental approach to SEM, which is a procedural design and sounds workable for testing simple models and presents an example to test a parsimonious model of MBA knowledge and skills transfer using SEM and multiple regression. The results indicate that only one significant relationship can be justified by multiple regression. SEM, on the other hand, has helped to develop new relationships based on the modification indexes, which are also theoretically accepted. Finally, three relationships are shown to be significant and the "best fitting" structural model has been established. Copyright © 2001 MCB University Press.
Original languageEnglish
Pages (from-to)650-667
JournalJournal of Management Development
Volume20
Issue number7
DOIs
Publication statusPublished - 2001

Citation

Cheng, E. W. L. (2001). SEM being more effective than multiple regression in parsimonious model testing for management development research. Journal of Management Development, 20(7), 650-667. doi: 10.1108/02621710110400564

Keywords

  • Research
  • Management development
  • Model
  • Tests
  • Multiple regression analysis

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