Structural Equation Modeling in the Communication Sciences, 1995-2000

R. Lance Holbert · Michael T. Stephenson

358 citations0/0 files storedHuman Communication Research

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Psychometric Methodologies and Testing Statistical Methods and Applications Diverse Academic Research Areas

Abstract

Structural equation modeling (SEM) is a viable multivariate tool used by communication researchers for the past quarter century. Building off Cappella (1975) as well as McPhee and Babrow (1987), this study summarizes the use of this technique from 1995–2000 in 37 communication-based academic journals. We identify and critically assess 3 unique methods for testing structural relationships via SEM in terms of the specification, estimation, and evaluation of their respective structural equation models. We provide general guidelines for the use of SEM and make recommendations concerning latent variable models, sample size, reporting parameter estimates, model fit statistics, cross-sectional data, univariate normality, cross-validation, nonrecursive modeling, and the decomposition of effects (direct, indirect, and total).

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References

1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 1988Structural equation modeling in practice: A review and recommended two-step approach.1998Principles and Practice of Structural Equation Modeling 1992Alternative Ways of Assessing Model Fit 1990Comparative fit indexes in structural models.1989Structural Equations with Latent Variables 1991Structural Equations with Latent Variables.1994Testing Structural Equation Models.

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