Operates on item correlation matrix
Asks how many dimensions underpin a questionnaire or rating scale.
Reduces large number of correlations to small number of factors
Correlation reflects relationship between 2 variables
Ranges from -1 to +1
Factor Analysis
Visual Perception, Cubes, Lozenges, Paragraph Comprehension, Sentence
Completion, Word Meaning, Addition, Count-the-Dots, Straight-curved Caps
Holzinger & Swineford (1939)
Principal Components Analysis (PCA)
Descriptive
- Explore the underlying structure of constructs (components)
Steps to FA
Suitability of questions / items
•A communality of a variable that is 0.75 is very good, but also it should load to an
interpretable factor.
•Variables with communalities below 0.50 are usually dropped (or extract more factors)