Relations between variables can take different forms like linearity, piecewise linearity, or nonlinearity. Segmented regression analyses (SRA) are specialized statistical methods that detect breaks in the relationship between variables. They are commonly used in the social sciences for exploratory analyses. However, many relations may not be best described by a breakpoint and a resulting piecewise linear relation, but rather by a nonlinearity. In the present simulation study, we examined the application of SRA-specifically the Davies test-in the presence of various forms of nonlinearity. We found that moderate and strong degrees of nonlinearity led to a frequent identification of statistically significant breakpoints and that the identified breakpoints were widely distributed. The results clearly indicate that SRA cannot be used for exploratory analyses. We propose alternative statistical methods for exploratory analyses and outline the conditions for the legitimate use of SRA in the social sciences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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为什么使用分段回归分析来探索变量之间关系的变化是有问题的：模拟研究。

变量之间的关系可以采用不同的形式，如线性、分段线性或非线性。分段回归分析 (SRA) 是专门的统计方法，用于检测变量之间关系的中断。它们通常用于社会科学中的探索性分析。然而，许多关系可能无法通过断点和由此产生的分段线性关系来最好地描述，而只能通过非线性来描述。在当前的模拟研究中，我们检查了 SRA 在各种形式的非线性存在下的应用，特别是戴维斯检验。我们发现中度和强度的非线性导致频繁识别具有统计显着性的断点，并且所识别的断点分布广泛。结果清楚地表明 SRA 不能用于探索性分析。我们提出了用于探索性分析的替代统计方法，并概述了在社会科学中合法使用 SRA 的条件。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。