The relative weight analysis is a classic tool to detect if one variable or interaction in a model is relevant or not. In this paper, we will 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 treating control, fixed, free and interactions terms at the same time in the residual weight analysis. The interactions are residualized properly against their main effects to keep their true effect in the model. We test this method with two simulated examples.

翻译：相对权重分析是一个典型的工具,用来检测模型中的一个变量或互动是否相关。在本文中,我们将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便于使用的方法,分析多变量模型,并用最具代表性的一组变量确定一个子集。此外,我们制定了一个程序,同时处理剩余权重分析中的控制、固定的、自由的和互动条件。这些互动结合其主要影响进行适当处理,以保持其在模型中的真实效果。我们用两个模拟的例子测试这一方法。