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semopy: A Python Package for Structural Equation Modeling

178 citations0/0 files storedStructural Equation Modeling A Multidisciplinary Journal

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Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Computational Physics and Python Applications

Abstract

Structural equation modeling (SEM) is a multivariate statistical technique for estimating complex relationships between observed and latent variables. Although numerous SEM packages currently exist, they each have limitations and more importantly they are not free or open-source. The only package that is both free and open-source is lavaan. However, because this package is written in R, it is often difficult to integrate it with other programming language functionalities. This paper provides an overview of a new Python package called semopy that was specifically developed to overcome these limitations. Using illustrative examples we introduce the new package and then compare its performance in accuracy and execution time to lavaan.

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References

1999Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives 2012lavaan : An R Package for Structural Equation Modeling 1989Structural Equations with Latent Variables 1969A General Approach to Confirmatory Maximum Likelihood Factor Analysis 2006Structural Equation Modeling and Natural Systems 2015OpenMx 2.0: Extended Structural Equation and Statistical Modeling 1984Maximum Likelihood Estimation of Models for Residual Covariance in Spatial Regression 2005Polychoric and Polyserial Correlations

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