# Factor Analysis & SEM

### Conduct and Interpret a Factor Analysis

What is the Factor Analysis? The Factor Analysis is an explorative analysis. Much like the cluster analysis grouping similar cases, the factor analysis groups similar variables into dimensions. This process is also called identifying latent variables. Since factor analysis is an explorative analysis it does not distinguish between independent and dependent variables. Factor Analysis reduces

### PLS Graph Software

PLS graph is an application that consists of a windows based graphical user interface that helps the researcher or the user to perform partial least square (PLS) analyses. PLS analysis provides a general model which helps in predictive analyses (usually in pilot studies), such as canonical correlations, multiple regressions, MANOVAs, and PCAs. It helps the

### LISREL

LISRELis a program application provided by Windows for performing structural equation modeling (SEM), and other related linear structure modeling (e.g.,multilevel structural equation modeling, multilevel linear and non-linear modeling, etc.). LISREL for Windows is helpful in importing the external data in various formats like SPSS, SAS , MS Excel, etc. as a PRELIS system file (PSF).

### Structural Equation Modeling

Structural equation modeling is a multivariate statistical analysis technique that is used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is used to analyze the structural relationship between measured variables and latent constructs. This method is preferred by the researcher because it estimates the multiple

### Principal Component Analysis (PCA)

There are two basic approaches to factor analysis: principal component analysis (PCA) and common factor analysis. Overall, factor analysis involves techniques to help produce a smaller number of linear combinations on variables so that the reduced variables account for and explain most the variance in correlation matrix pattern. Principal component analysis is an approach to

### Path Analysis

Path analysis is an extension of the regression model. In a path analysis model from the correlation matrix, two or more casual models are compared. The path of the model is shown by a square and an arrow, which shows the causation. Regression weight is predicated by the model. Then the goodness of fit statistic

### Factor Analysis

Factor analysis is a technique that is used to reduce a large number of variables into fewer numbers of factors. This technique extracts maximum common variance from all variables and puts them into a common score. As an index of all variables, we can use this score for further analysis. Factor analysis is part of

### Exploratory Factor Analysis

Exploratory factor analysis is a statistical technique that is used to reduce data to a smaller set of summary variables and to explore the underlining theoretical structure of the phenomena. It is used to identify the structure of the relationship between the variable and the respondent. Exploratory factor analysis can be performed by using the

### Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is a multivariate statistical procedure that is used to test how well the measured variables represent the number of constructs. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) are similar techniques, but in exploratory factor analysis (EFA), data is simply explored and provides information about the numbers of factors required