Workshop on Advanced Data Analysis through Structural Equation Modeling (SEM)
A workshop on Advanced Data Analysis through Structural Equation Modeling (SEM) was organized by Research Cell of Jaipuria Institute of Management, Noida on 18th December 2015. The workshop was attended by Dr Nimit Gupta, Associate Professor, Fortune Institute of International Business (FIIB). The workshop was facilitated by Prof. Pankaj Medhi who briefed the participants about Structural Equation Model (SEM) and Analysis of Moment Structures (AMOS) software which is an add-on module for Statistical Package for the Social Sciences (SPSS). Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA) were discussed in much detail. Explanations on the critical tools and factors using Bootstrapping were also done in detail.
18th December 2015
AMOS is statistical software and it stands for analysis of a moment structures. AMOS is an added SPSS module, and is specially used for Structural Equation Modeling, path analysis, and confirmatory factor analysis. It is also known as analysis of covariance or causal modeling software. AMOS is a visual program for structural equation modeling (SEM). In AMOS, we can draw models graphically using simple drawing tools. AMOS quickly performs the computations for SEM and displays the results.
Confirmatory factor analysis (CFA) is a statistical technique used to verify the factor structure of a set of observed variables. CFA allows the researcher to test the hypothesis that a relationship between observed variables and their underlying latent constructs exists. Exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within analysis whose overarching goal is to identify the underlying relationships between measured variables. It is commonly used by researchers when developing a scale (a scale is a collection of questions used to measure a particular research topic) and serves to identify a set of latent constructs underlying a battery of measured variables.
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