Which analysis identifies clusters of related items and reveals the underlying dimensions of performance?

• A. Factor analysis
• B. Cronbach's alpha
• C. External reliability
• D. Internal reliability

Answer: (A)

To identify clusters of related items and reveal the underlying dimensions of performance, you would use factor analysis. This approach looks at how items correlate with each other and groups together those that vary together into factors, each representing a latent dimension or construct. By examining which items load onto which factors, you can see the structure of what a test is measuring—whether it taps into several distinct abilities or a single overarching skill. In exploratory factor analysis, the data itself suggests how many factors exist and which items belong to each factor; in confirmatory factor analysis, you test a predefined factor structure. Cronbach's alpha and internal reliability, on the other hand, assess whether items hang together as a single, coherent scale rather than revealing multiple underlying dimensions.