Title: Use Structural Equation Modeling: Theory and Application When we have latent variables in our research, the only suitable procedure is Structural Equation Modeling (SEM). This procedure is specifically designed to measure the unobserved variables which cannot be observed directly. There are times that we cannot solve the research problems using only the observed variables. Thus, SEM procedure is the answer for this. In this book, the writer explains two types of SEM, namely Covariance Based Structural Equation Modeling (CBSEM) and Partial Least Square Based Structural Equation Modeling (PLS SEM). The first one is mainly for the normally distributed data and the second one is for the non - normally distributed data. The calculation of CBSEM will be assisted using LISREL and PLS SEM will be assisted using Smart PLS. This book will discuss the following matters: • Part I: Covariance Based Structural Equation Modeling (CBSEM) o Basics: this will cover the definition, basic concept, history, uses, underlying assumption, and index of goodness of fit of the model. o General Models in CBSEM: this will explain about several models in CBSEM, such as Confirmatory Factor Analytic Model (CFA), Second Order CFA Model and Full Latent Variable Model (LV) as well as the structural model and measurement model. o Application in Data Analysis: it will give some examples in the research concerning the relationship among the variables we study, such as an exogenous and endogenous variable model, an exogenous and endogenous variable model with the intervening variable; and an exogenous and endogenous variable model with moderation. • Part II: Partial Least Square Based Structural Equation Modeling (PLS SEM) o Basic concepts, the underlying assumption and theoretical backgrounds o The variables’ relationship model as the departure of using the PLS SEM o Application in Data Analysis: it will expose several models, such as an exogenous and endogenous variable model, an exogenous and endogenous variable model with the intervening variable; and an exogenous and endogenous variable model with moderation. • The Differences and Similarities between CB SEM and PLS SEM • The examples are taken from the actual research models. • Exercises

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