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2016•Unpublished venueOpen access

Structural Equation Modeling

Kohei Adachi

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Abstract

In confirmatory factor analysis (CFA), introduced in the previous chapter, all factors (latent variables) were the causes (explanatory variables). An extended variant of CFA is structural equation modeling ( SEM ), in which the causal relationships among factors are considered; i.e., factors appear that are dependent variables . These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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What this paper is about

In confirmatory factor analysis (CFA), introduced in the previous chapter, all factors (latent variables) were the causes (explanatory variables). An extended variant of CFA is structural equation modeling ( SEM ), in which the causal relationships among factors are considered; i.e., factors appear that are dependent variables . These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In confirmatory factor analysis (CFA), introduced in the previous chapter, all factors (latent variables) were the causes (explanatory variables). An extended variant of CFA is structural equation modeling ( SEM ), in which the causal relationships among factors are considered; i.e., factors appear that are dependent variables . These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Key concepts: Structural equation modeling, Latent variable, Confirmatory factor analysis, Econometrics, Variable (mathematics), Latent variable model, Causal model, Mathematics

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