The proportion of a variable's variance that is common variance; this term is used primarily in factor analysis.

• A. Common variance
• B. Concurrent validity
• C. Confidence interval
• D. Communality

Answer: (D)

Communality is the portion of a variable’s variance that is shared with other variables and explained by the common factors in a factor-analysis model. In factor analysis, each variable’s total variance splits into two parts: common variance (shared with other variables through the latent factors) and unique variance (specific to the variable and measurement error). The communality (often denoted h^2) represents how much of a variable’s variance is accounted for by those underlying factors. The higher the communality, the more the variable is represented by the factor solution. Other terms listed don’t fit this specific concept: concurrent validity relates to how well a test correlates with a criterion measured at the same time, and a confidence interval concerns estimation precision. The phrase “common variance” describes the idea, but the standard label used in factor analysis is communality.