ABSTRACT
Among structural equation modeling (SEM) techniques, by far the most well known are covariance-based methods as exemplified by software such as LISREL, EQS, AMOS, SEPATH, and RAMONA. In fact, to many social science researchers, the covariance-based procedure is tautologically synonymous with the term SEM. Yet, an alternative and less widespread technique known as partial least squares (PLS) is also available for researchers interested in doing SEM-based analysis. Depending on the researcher’s objectives and epistemic view of data to theory, properties of the data at hand, or level of theoretical knowledge and measurement development, the PLS approach can be argued to be more suitable.
