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Using R Package gesca for generalized structured component analysis

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Abstract

The R package gesca was recently released to implement generalized structured component analysis (GSCA). GSCA represents a component-based approach to structural equation modeling (SEM) that defines a latent variable as a component or weighted composite of indicators. gesca enables users to obtain overall and local measures of model fit, parameter estimates with bootstrapped standard errors and confidence intervals, and the total and indirect effects of latent variables and indicators. It can also implement several basic extensions of GSCA, including constrained single- and multiple-group analysis, and second-order latent variable modeling. Furthermore, users easily specify their hypothesized relationships among latent variables and/or indicators based on an intuitive text-based syntax that comprises indicator names and simple numerical operators. Owing to its analytic versatility and ease of use, the package can be attractive to those wishing to apply GSCA to their research. This article provides step-by-step guidance on using the package with real examples.

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Notes

  1. To learn more about the dataset, refer to pages 112 to 119 in Chapter 3 of Hwang and Takane (2014).

  2. https://cran.r-project.org/web/packages/gesca/gesca.pdf.

  3. The letter a here has no intrinsic meaning. It only matters that the same two lowercase letters of the English alphabet be used as a convention for indicating that a parameter is constrained to be equal across groups. A different letter should be used for each instance of the c() statement within the same model specification.

  4. GSCA can accommodate both reflective and formative relationships between second- and first-order latent variables. Thus, either (θ)   = : or  = : (or equivalently, (1)   = : ) can be applied in the model syntax.

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Authors and Affiliations

  1. Department of Psychology, McGill University, 1205 Dr. Penfield Avenue, Montreal, QC, H3A 1B1, Canada

    Sunmee Kim, Ramsey Cardwell & Heungsun Hwang

Authors
  1. Sunmee Kim
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  2. Ramsey Cardwell
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  3. Heungsun Hwang
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Corresponding author

Correspondence to Sunmee Kim.

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On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Communicated by Shohei Shimizu.

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Kim, S., Cardwell, R. & Hwang, H. Using R Package gesca for generalized structured component analysis. Behaviormetrika 44, 3–23 (2017). https://doi.org/10.1007/s41237-016-0002-8

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