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

ISBN-10: 1452217440

ISBN-13: 9781452217444

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

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KEY TERMS CB-SEM: see Covariance-based structural equation modeling. Coding: is the assignment of numbers to scales in a manner that facilitates measurement. Confirmatory: see Confirmatory applications. Chapter 1 An Introduction to Structural Equation Modeling 29 Confirmatory applications: aim at empirically testing theoretically developed models. Constructs (also called latent variables): measure concepts that are ab­ stract, complex, and cannot be directly observed by means of (multiple) items.

Chapter 7 offers additional details on mediation and explains how to test mediating effects in PLS-SEM. Moderation Related to the concept of mediation is moderation. With modera­ tion, the construct could also directly affect the relationship between the exogenous and endogenous latent variables but in a different way. Referred to as a moderator effect, this situation occurs when the mod­ erator (an independent variable or construct) changes the strength or even the direction of a relationship between two constructs in the model.

They stem from the same domain), indicators associated with a particular construct should be highly correlated with each other. In addition, individual items should be interchangeable, and any single item can generally be left out without changing the meaning of the construct, as long as the construct has sufficient reliability. , because of a change in the standard of comparison), all indicators will change simultaneously. A set of reflective measures is commonly called a scale. In contrast, formative measurement models (also referred to as Mode B measurement in PLS-SEM) are based on the assumption that the indicators cause the construct.

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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Josephb F. Hair, G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt

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