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Table Of Contents
  • AMOS Graphics
  • Path Analysis
  • Latent Growth Curve (LGC) Modeling in AMOS
  • Confirmatory Factor Analysis (CFA)

AMOS Graphics

AMOS or Analysis of Moment Structures is an added SPSS module that supports path analysis confirmatory factor analysis (CFA), and structural equation modeling (SEM). It is a visual software that can be used to graphically draw models. AMOS boasts of simple drawing tools that can be used to perform structural equal modeling computations and display results. AMOS graphics uses methods such as generalized least squares, maximum likelihood, and Browne’s asymptotically distribution-free criterion, to compute SEM coefficients.

Path Analysis

Path analysis can be seen as an extension of an ordinary regression model. It is used to compare two or more causal models from the correlation matrix. Path analysis uses an arrow and a square to depict the path of the model. AMOS allows you to carry out path analysis on several regression models

Latent Growth Curve (LGC) Modeling in AMOS

LGC modeling is an SEM technique used to examine longitudinal change over time. This type of analysis allows users to examine:

Intra-individual changes

These changes occur within the same individual over time. A good example is a change in attitude.

Inter-individual differences

The differences between people can be seen at any given time. For example, the level of knowledge among participants of an interview.

Linear and non-linear changes

These changes are a combination of intra-individual and inter-individual changes.

To understand the underlying features of latent growth curve modeling, you must have a foundational knowledge of structural equation modeling.

Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis is used to estimate how well the number of constructs is represented by the variables that have been measured. This multivariate statistical procedure is almost similar to exploratory factor analysis (EFA). However, EFA provides details on the factors that are required to represent data by simply exploring data. Researchers can use CFA to determine the number of factors needed for their data. It is a technique that is used to reject or confirm the theory of measurement.