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1 year ago in Conceptualization By Rhetamed

Compare and contrast the philosophical and statistical objectives of SmartPLS (prediction-oriented, variance-explained) versus AMOS (theory confirmation, covariance-fitting). When would you choose one over the other for your research?

Compare the philosophical and statistical goals of SmartPLS, which is prediction-oriented and focuses on explained variance, with those of AMOS, which emphasizes theory testing and covariance fitting. In what research scenarios would you choose one method over the other?

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By Amardeep Singh Answered 7 months ago

SmartPLS adopts a variance-based, prediction-oriented approach aimed at maximizing the explained variance (R²) in dependent constructs, making it ideal for exploratory theory development. In contrast, AMOS employs a covariance-based, theory-confirmation approach, rigorously testing how well a hypothesized model reproduces the observed covariance matrix. Choose SmartPLS for complex, predictive models with non-normal data or formative constructs. Choose AMOS for confirming established theories with normally distributed data and a focus on overall model fit.  

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