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In statistics, the principle of marginality refers to the fact that the average (or main) effects, of variables in an analysis are ''marginal'' to their interaction effect. The principle of marginality argues that, in general, it is wrong to test, estimate, or interpret main effects of explanatory variables where the variables interact or, similarly, to model interaction effects but delete main effects that are marginal to them.〔Fox, J. (Regression Notes ).〕 While such models are interpretable, they lack applicability, as they ignore the effects of their marginal main effects. Nelder and Venables〔Venables, W.N. (1998). ("Exegeses on Linear Models" ). Paper presented to the S-PLUS User’s Conference Washington, DC, 8–9 October 1998.〕 have argued strongly for the importance of this principle in regression analysis. ==See also== * General linear model * Analysis of variance 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「Principle of marginality」の詳細全文を読む スポンサード リンク
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