Common Factor Variance
- Measures how much variation in multiple variables is attributable to a single shared cause.
- Commonly applied in psychological and sociological research to interpret correlations among measures.
- Helps identify whether a single latent factor might be driving observed relationships.
Definition
Section titled “Definition”Common factor variance is a statistical concept that refers to the amount of variation in a set of variables that can be explained by a common underlying factor.
Explanation
Section titled “Explanation”Common factor variance quantifies the portion of observed variability across multiple variables that is attributable to one shared, latent factor. When variables are correlated, part of that correlation may reflect influence from the same underlying cause; common factor variance captures that shared component. This concept is frequently used in fields such as psychology and sociology to investigate relationships among measures and to infer possible latent drivers of those relationships.
Examples
Section titled “Examples”Job satisfaction and job performance
Section titled “Job satisfaction and job performance”Consider a study on the relationship between job satisfaction and job performance. Researchers might measure both constructs using standardized scales and analyze whether they correlate. If a significant correlation exists, a common underlying factor (for example, motivation or job satisfaction) might be driving both measures; the common factor variance is the amount of variation in the two variables explained by that shared factor.
Personality traits and health
Section titled “Personality traits and health”In a study relating personality traits and health, researchers might measure extroversion and agreeableness alongside health outcomes such as blood pressure and body mass index. If significant correlations appear between the personality traits and health outcomes, a common underlying factor (for example, stress or coping skills) could be influencing both sets of variables; the common factor variance denotes how much variation is explained by that factor.