Moderation (statistics)
In statistics and regression analysis, moderation occurs when the relationship between two variables depends on a third variable. The third variable is referred to as the moderator variable or simply the moderator. The effect of a moderating variable is characterized statistically as an interaction; that is, a qualitative (e.g., sex, race, class) or quantitative (e.g., level of reward) variable that affects the direction and/or strength of the relation between dependent and independent variables. Specifically within a correlational analysis framework, a moderator is a third variable that affects the zero-order correlation between two other variables. In analysis of variance (ANOVA) terms, a basic moderator effect can be represented as an interaction between a focal independent variable and a factor that specifies the appropriate conditions for its operation.
Read more about Moderation (statistics): Example, Multicollinearity in Moderated Regression, Post-hoc Probing of Interactions, See Also
Famous quotes containing the word moderation:
“After mature deliberation of counsel, the good Queen to establish a rule and imitable example unto all posterity, for the moderation and required modesty in a lawful marriage, ordained the number of six times a day as a lawful, necessary and competent limit.”
—Michel de Montaigne (1533–1592)