Which statistical technique is often used to analyze the internal structure of an assessment instrument?

Factor analysis is the statistical technique commonly used to analyze the internal structure of an assessment instrument. This method allows researchers and analysts to identify underlying relationships between various items or variables in a dataset, helping to determine how they group together to form broader constructs or factors.

In the context of assessment instruments, factor analysis can reveal how well different questions or tasks correlate with one another, which can inform the validity and reliability of the instrument as a whole. Understanding these relationships is essential for ensuring that the assessment effectively measures the intended constructs.

Other statistical methods mentioned, such as regression analysis, variance analysis, and descriptive statistics, serve different purposes. Regression analysis focuses on modeling the relationship between dependent and independent variables to make predictions. Variance analysis, often used in experimental contexts, examines the differences between group means. Descriptive statistics summarize data characteristics but do not explore relationships within the data. Thus, factor analysis is distinctly suited for exploring the internal structure of assessments.