Relative weight analysis is a classic tool for detecting whether one variable or interaction in a model is relevant. In this study, we focus on the construction of relative weights for non-linear interactions using restricted cubic splines. Our aim is to provide an accessible method to analyze a multivariate model and identify one subset with the most representative set of variables. Furthermore, we developed a procedure for treating control, fixed, free and interaction terms simultaneously in the residual weight analysis. The interactions are residualized properly against their main effects to maintain their true effects in the model. We tested this method using two simulated examples.

翻译：相对权重分析是一个典型的工具,用来检测模型中一个变量或互动是否相关。在本研究中,我们侧重于使用限制的立方样条构建非线性互动的相对权重。我们的目标是提供一种无障碍的方法,分析多变量模型,并用最有代表性的变量组确定一个子集。此外,我们制定了一个程序,在剩余权重分析中同时处理控制、固定、自由和互动术语。这些互动结合其主要效应进行适当处理,以便在模型中保持其真实效果。我们用两个模拟实例测试了这一方法。