图1. 以3组解释变量X₁、X₂和X₃为例, 使用韦恩图概括了响应变量Y的总变差组成。A, 基于变量的顺序R²的方法, 根据分配的顺序, [a]、[b]和[c]分别为X₁、X₂和X₃的条件效应。B, 基于变差分解和层次分割法, [a]、[b]和[c]分别为X₁、X₂和X₃的边际效应, [d]、[e]和[f]分别为X₁、X₂和X₃两两之间的共同效应, [g]为三者之间的共同效应, X₁、X₂和X₃的单独效应分别为[a] + [d]/2 + [f]/2 + [g]/3、[b] + [d]/2 + [e]/2 + [g]/3以及[c] + [e]/2 + [f]/2 + [g]/3。残差[h]代表了未被X₁、X₂和X₃解释的Y的变差部分。

Fig. 1. Venn diagram representing the variation composition of a response matrix Y regressed against three correlated predictors of X₁, X₂, and X₃. A, According to the order of assignment, [a], [b] and [c] are the conditional effect of X₁, X₂ and X₃, respectively. B, Based on variation partitioning and hierarchical partitioning, [a], [b] and [c] are the marginal effect of X₁, X₂ and X₃, respectively; [d], [e] and [f] are the common effect of X₁, X₂ and X₃, respectively; [g] is the common effect among X₁, X₂ and X₃; the individual effect of X₁, X₂ and X₃ can be expressed as [a] + [d]/2 + [f]/2 + [g]/3, [b] + [d]/2 + [e]/2 + [g]/3 and [c] + [e]/2 + [f]/2 + [g]/3. Residual [h] represents the fraction of Y that is not explained by X₁, X₂ or X₃.