Practical Guide of the Integrated Structural Equation Modeling (SEM) with LISREL and AMOS for Marketing & Social Sciences Thesis

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Buku ini terdiri dari beberapa bab Bab pertama membahas tentang what is structural equation modeling bab dua tentang why is structural equation modeling SEM bab tiga tentang basic concept of structural equation modeling SEM dan bab empat tentang SEM procedure Adapun bab lima membahas tentang tutorial bab enam tentang SEM tutorial with LISREL bab tujuh tentang SEM tutorial with AMOS dan bab yang terakhir bab delapan tentang statistical results comparation LISREL VS AMOS Let s discuss one by one It is very clear now that univariate is only involving a single variable For instance we just want to investigate the brand image in a hospital We would study and explore the brand image only in that hospital Then we have to use univariate technique We would receive the data as the results and we name it as univariate data Univariate data does not deal with causes or relationship We would not see any relationship in the univariate data It is because the major purpose of univariate analysis is only taking data summarizing and describing data On the other hand bivariate is only involving two factors or variables It deals with causes or relationship but only between the two variables The major purpose of bivariate analysis is explaining and examining two variables simultaneously Many often researchers are having a set of interrelated questions in their study Yet none of the other of multivariate technique enable researchers to investigate the questions with one integrated technique Hair et al 2007 Multiple regression factor analysis multivariate analysis of variance MANOVA discriminant analysis and other techniques can only examine the relationship in a single relationship at a time Even the techniques allowing for multiple dependent variables such as MANOVA and canonical analysis they are still examining only a single relationship between the dependent and independent variables Buku ini terdiri dari beberapa bab Bab pertama membahas tentang what is structural equation modeling bab dua tentang why is structural equation modeling SEM bab tiga tentang basic concept of structural equation modeling SEM dan bab empat tentang SEM procedure Adapun bab lima membahas tentang tutorial bab enam tentang SEM tutorial ...with LISREL bab tujuh tentang SEM tutorial with AMOS dan bab yang terakhir bab delapan tentang statistical results comparation LISREL VS AMOS Let s discuss one by one It is very clear now that univariate is only involving a single variable For instance we just want to investigate the brand image in a hospital We would study and explore the brand image only in that hospital Then we have to use univariate technique We would receive the data as the results and we name it as univariate data Univariate data does not deal with causes or relationship We would not see any relationship in the univariate data It is because the major purpose of univariate analysis is only taking data summarizing and describing data On the other hand bivariate is only involving two factors or variables It deals with causes or relationship but only between the two variables The major purpose of bivariate analysis is explaining and examining two variables simultaneously Many often researchers are having a set of interrelated questions in their study Yet none of the other of multivariate technique enable researchers to investigate the questions with one integrated technique Hair et al 2007 Multiple regression factor analysis multivariate analysis of variance MANOVA discriminant analysis and other techniques can only examine the relationship in a single relationship at a time Even the techniques allowing for multiple dependent variables such as MANOVA and canonical analysis they are still examining only a single relationship between the dependent and independent variables

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