Structural equation modeling SEM is becoming the central and arguably most popular analytical tool in social sciences. Many classical and modern statistical techniques such as regression analysis, path analysis, confirmatory factor analysis, and models with both measurement and structural components have Many classical and modern statistical techniques such as regression analysis, path analysis, confirmatory factor analysis, and models with both measurement and structural components have been shown to fall under the umbrella of SEM. The flexibility of SEM makes it applicable to many research designs, including experimental and non-experimental data, cross-sectional and longitudinal data, and multiple-group and multilevel problems.
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A new criterion for assessing discriminant validity in variance-based structural equation modeling
Metrics details. Structural equation modeling SEM is a set of statistical techniques used to measure and analyze the relationships of observed and latent variables. Similar but more powerful than regression analyses, it examines linear causal relationships among variables, while simultaneously accounting for measurement error. The purpose of the present paper is to explicate SEM to medical and health sciences researchers and exemplify their application.
The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling PLS-SEM from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field. Based on bibliometric data downloaded from the Web of Science, the authors apply various social network analysis SNA and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically, the authors investigate the PLS-SEM knowledge network by analyzing 84 methodological studies published in 39 journals by authors from institutions. Besides presenting the results of a country level analysis, the research also identifies journals that play a key role in disseminating knowledge in the network.