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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 categorical (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, or the value of the slope of the dependent variable on the independent variable. 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.〔Baron, R. M., & Kenny, D. A. (1986). "The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations", ''Journal of Personality and Social Psychology,'' 5 (6), 1173–1182 (page 1174)〕 ==Example== Moderation analysis in the behavioral sciences involves the use of linear multiple regression analysis or causal modelling.〔 To quantify the effect of a moderating variable in multiple regression analyses, regressing random variable ''Y'' on ''X'', an additional term is added to the model. This term is the interaction between ''X'' and the proposed moderating variable.〔 Thus, for a response ''Y'' and two variables ''x''1 and moderating variable ''x''2,: : In this case, the role of ''x''2 as a moderating variable is accomplished by evaluating ''b''3, the parameter estimate for the interaction term.〔 See linear regression for discussion of statistical evaluation of parameter estimates in regression analyses. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Moderation (statistics)」の詳細全文を読む スポンサード リンク
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