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Journal Photo for Structural Equation Modeling: A Multidisciplinary Journal
Peer reviewed only Open Access

Structural Equation Modeling: A Multidisciplinary Journal (SEMM)

Publisher : Taylor & Francis, Inc
Sociology Political Science Modeling
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e-ISSN 1532-8007
p-ISSN 1070-5511
Issue Frequency Monthly
Impact Factor 5.9
Est. Year 1994
Mobile 18003541420
Country United States
Language English
APC YES
Impact Factor Assignee Google Scholar
Email enquiries@taylorandfrancis.com

Journal Descriptions

Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.

Structural Equation Modeling: A Multidisciplinary Journal (SEMM) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Sociology, Political Science, Modeling, Simulation, Economics, Econometrics and Finance, Decision Sciences , Online or Print , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 1070-5511, E-ISSN: 1532-8007, Established: 1994, Impact Factor: 5.9
  • Does Not Provide Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Publications of SEMM

Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives
Peter M. Bentler March, 1999
This article examines the adequacy of the “rules of thumb” conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice. Using...
Enhancing Model Fit Evaluation in SEM: Practical Tips for Optimizing Chi-Square Tests
Peter M. Bentler January, 2025
This paper aims to advocate for a balanced approach to model fit evaluation in structural equation modeling (SEM). The ongoing debate surrounding chi-square test statistics and fit indices h...
RGLS and RLS in Covariance Structure Analysis
Peter M. Bentler March, 2023
This paper assesses the performance of regularized generalized least squares (RGLS) and reweighted least squares (RLS) methodologies in a confirmatory factor analysis model. Normal theory ma...
40-Year Old Unbiased Distribution Free Estimator Reliably Improves SEM Statistics for Nonnormal Data
Peter M. Bentler June, 2022
In structural equation modeling, researchers conduct goodness-of-fit tests to evaluate whether the specified model fits the data well. With nonnormal data, the standard goodness-of-fit test ...
Testing Mean and Covariance Structures with Reweighted Least Squares
Peter M. Bentler October, 2021
Chi-square tests based on maximum likelihood (ML) estimation of covariance structures often tend to over-reject the null hypothesis, Σ = Σθ, particularly when the sample size is small. Re...
Distributionally-Weighted Least Squares in Growth Curve Modeling
Peter M. Bentler January, 2022
Growth curve modeling is a widely used technique in psychological, educational, and social science research. While mainstream estimators for growth curve modeling are based on normal theory,...
Number of Factors in Growth Curve Modeling
Peter M. Bentler March, 2018
Basic growth curve models parameterize the mean and covariance structure of a set of repeated measures by latent factors that represent the polynomial influences of time. In practice it may ...
Teacher's Corner: Testing Measurement Invariance of Second-Order Factor Models
Stephen G. West November, 2009
We illustrate testing measurement invariance in a second-order factor model using a quality of life dataset (n = 924). Measurement invariance was tested across 2 groups at a set of hierarchi...
Effects of sample size and nonnormality on the estimation of mediated effects in latent variable models
Stephen G. West November, 2009
A Monte Carlo approach was used to examine bias in the estimation of indirect effects and their associated standard errors. In the simulation design, (a) sample size, (b) the level of nonnor...
Level-Specific Evaluation of Model Fit in Multilevel Structural Equation Modeling
Ehri Ryu October, 2009
In multilevel structural equation modeling, the “standard” approach to evaluating the goodness of model fit has a potential limitation in detecting the lack of fit at the higher level. L...