Stats File

Factor Analysis

Principal components factor analysis

Use of extracted factors in multivariate dependency models

KEY CONCEPTS
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Factor Analysis

Interdependency technique
Assumptions of factor analysis
Latent variable (i.e. factor)
Research questions answered by factor analysis
Applications of factor analysis
Exploratory applications
Confirmatory applications
R factor analysis
Q factor analysis
Factor loadings
Steps in factor analysis
Initial v final solution
Factorability of an intercorrelation matrix
Bartlett's test of sphericity and its interpretation
Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and its interpretation
Identity matrix and the determinant of an identity matrix
Methods for extracting factors
Principal components
Maximum likelihood method
Principal axis method
Unwieghted least squares
Generalized least squares
Alpha method
Image factoring
Criteria for determining the number of factors
Eigenvalue greater than 1.0
Cattell's scree plot
Percent and cumulative percent of variance explained by the factors extracted
Component matrix and factor loadings
Communality of a variable
Determining what a factor measures and naming a factor
Factor rotation and its purpose
      Varimax
Quartimax
Equimax
Orthogonal v oblique rotation
Reproduced correlation matrix
Computing factor scores
Factor score coefficient matrix
Using factor score in multivariate dependency models

Lecture Outline

✓ Identifying patterns of intercorrelation

✓ Factors v correlations

✓ Steps in the factor analysis process

✓ Testing for "factorability"

✓ Initial v final factor solutions

✓ Naming factors

✓ Factor rotation

✓ Computing factor scores

✓ Using factors scores in multivariate dependency models
Factor Analysis

Interdependency Technique

      Seeks to find the latent factors that account for the patterns of collinearity among multiple metric variables

Assumptions...