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      Data generation for composite-based structural equation modeling methods

      Schlittgen, Rainer; Sarstedt, Marko; Ringle, Christian M.
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      Schlittgen2020_Article_DataGenerationForComposite-bas.pdf
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      DOI
       10.1007/s11634-020-00396-6
      Link
       link.springer.com
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      Schlittgen, R., Sarstedt, M., & Ringle, C. M. (2020). Data generation for composite-based structural equation modeling methods. Advances in Data Analysis and Classification. https://doi.org/10.1007/s11634-020-00396-6
      Permanent Research Commons link: https://hdl.handle.net/10289/13651
      Abstract
      Examining the efficacy of composite-based structural equation modeling (SEM) features prominently in research. However, studies analyzing the efficacy of corresponding estimators usually rely on factor model data. Thereby, they assess and analyze their performance on erroneous grounds (i.e., factor model data instead of composite model data). A potential reason for this malpractice lies in the lack of available composite model-based data generation procedures for prespecified model parameters in the structural model and the measurements models. Addressing this gap in research, we derive model formulations and present a composite model-based data generation approach. The findings will assist researchers in their composite-based SEM simulation studies.
      Date
      2020
      Type
      Journal Article
      Publisher
      Springer
      Rights
      © 2020, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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