Partial Least Square Structural Equation Modeling (PLS-SEM) / Nur Zainie Abd Hamid
Structural Equation Modeling (SEM) is a multivariate statistical analysis tool that is increasingly used to analyze structural relationship by the researcher in the business field. Two primary SEM techniques are Covariance-based Structural Equation Modeling (CB-SEM) and Partial Least Squares Structu...
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| Format: | Book Section |
| Language: | en |
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Faculty of Business & Management, Universiti Teknologi MARA (UiTM) Cawangan Kedah
2020
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| Online Access: | https://ir.uitm.edu.my/id/eprint/47723/1/47723.pdf https://ir.uitm.edu.my/id/eprint/47723/ |
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| Summary: | Structural Equation Modeling (SEM) is a multivariate statistical analysis tool that is increasingly used to analyze structural relationship by the researcher in the business field. Two primary SEM techniques are Covariance-based Structural Equation Modeling (CB-SEM) and Partial Least Squares Structural Equation Modeling (PLS-SEM). CB-SEM is primarily used to confirm or reject theories by determining how well a proposed theoretical model can estimate the covariance matrix for a sample dataset. On the other hand, PLS-SEM is primarily used to develop theories in exploratory research by explaining the variance in the dependent variables when examining the model. |
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