Abstract
Abstract Covariance structure modeling, also known as structural equation modeling or causal modeling, appears increasingly popular. Such techniques can be used to conduct tests of complex theory on empirical data. To conduct such tests, researchers need measures of known factor structure and the knowledge of structural relations among the constructs of interest. Researchers typically have neither the required measures nor the knowledge of structural relations. Instead of conducting tests of theory, researchers use covariance structure models to develop measurements and theoretical models. This paper discusses why such use of covariance structure models is unlikely to produce scientific progress and proposes some alternative procedures thought to be more fruitful.
Keywords
CovarianceStructural equation modelingCausal modelEconometricsCausal structureComputer scienceManagement scienceMathematicsMachine learningStatisticsEconomics
Affiliated Institutions
Related Publications
Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats1
A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of individuals, teams...
Mean and Covariance Structures (MACS) Analyses of Cross-Cultural Data: Practical and Theoretical Issues
Practical and theoretical issues are discussed for testing (a) the comparability, or measurement equivalence, of psychological constructs and (b) detecting possible sociocultura...
PLS-SEM: Indeed a Silver Bullet
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent construc...
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi s...
Structural equation modeling in practice: A review and recommended two-step approach.
In this article, we provide guidance for substantive researchers on the use of structural equation modeling in practice for theory testing and development. We present a comprehe...
Publication Info
- Year
- 1995
- Type
- article
- Volume
- 16
- Issue
- 3
- Pages
- 201-213
- Citations
- 344
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
344
OpenAlex
Cite This
Michael Τ. Brannick
(1995).
Critical comments on applying covariance structure modeling.
Journal of Organizational Behavior
, 16
(3)
, 201-213.
https://doi.org/10.1002/job.4030160303
Identifiers
- DOI
- 10.1002/job.4030160303