Download e-book for iPad: A Primer on Partial Least Squares Structural Equation by Josephb F. Hair, G. Tomas M. Hult, Christian M. Ringle,

By Josephb F. Hair, G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt

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Extra info for A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

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Path models: are diagrams that visually display the hypotheses and variable relationships that are examined when structural equation modeling is applied. PLS regression: is an analysis technique that explores the linear relation­ ships between multiple independent variables and a single or multiple dependent variable(s). In developing the regression model, it con­ structs composites from both the multiple independent variables and the dependent variable(s) by means of principal component analysis.

Likewise, it is possible to have alternative competing models that test a different sequence (Sattler, Volckner, Riediger, & Ringle, 2010; Wilson, Callaghan, Ringle, & Henseler, 2007). However, selecting the best sequence among several com­ peting alternatives can be challenging. When the sequence of the constructs has been decided, then the relationships between them must be established by drawing arrows. The arrows are inserted with the arrow pointed to the right. This approach indicates the sequence and that the constructs on the left predict the constructs to the right.

Explain the differences between reflective and formative measures and be able to specify the appropriate measurement model. 3. Explain the difference between multi-item and single-item measures and be able to assess when to use each measurement type. 4. Describe the data collection and examination considerations necessary to apply PLS-SEM. 5. Learn how to develop a PLS path model using the SmartPLS software. CHAPTER PREVIEW Chapter 2 introduces the basic concepts of structural and measure­ ment model specification when PLS-SEM is used.

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