Factor Analysis

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Factor Analysis is an analysis technique that seeks to describe the variation in a set of observed variables in terms of a smaller number of unobserved latent variables or factors. 

Factor Analysis

1. From an open JMP^® data table, select Analyze > Multivariate Methods > Factor Analysis.
2. Select continuous variables from Select Columns, and Click Y, Columns (continuous variables have blue triangles).
3. Click OK. JMP displays an Eigenvalue report and a Scree Plot, along with a Model Launch dialog. 
4. Click Go in the Model Launch dialog to run the factor analysis at the default settings. The following results are provided (additional options are available under the red triangles):

• Final communality estimates
• The variance explained by each factor
• Significance tests for the factor analysis
• Rotated factor loadings
• Factor loading plot

Tips:

• The default factoring method is Maximum Likelihood, the number of factors to extract is 2, and the rotation method is Varimax. These options can be changed in the Model Launch dialog (shown above).
• To save the factor scores as new columns to the data table, click on the red triangle and select Save Rotated Components.

Socioeconomic.jmp (Help > Sample Data Folder)

Interpretation of results:
• Factor 1 seems to be related to socioeconomic status, as Median House Value and Median School Years have large loadings on the factor.
• Factor 2 seems related to the labor force condition, as Total Population and Total Employment load highly on this factor.
• Professional Services loads on both factors.

Visit Multivariate Methods > Factor Analysis in JMP Help to learn more.