Mediation analysis is one of the most widely used statistical techniques in the social, behavioral, and medical sciences. Mediation models allow to study how an independent variable affects a dependent variable indirectly through one or more intervening variables, which are called mediators. The analysis is often carried out via a series of linear regressions, in which case the indirect effects can be computed as products of coefficients from those regressions. Statistical significance of the indirect effects is typically assessed via a bootstrap test based on ordinary least squares estimates. However, this test is sensitive to outliers or other deviations from normality assumptions, which poses a serious threat to empirical testing of theory about mediation mechanisms. The R package robmed implements a robust procedure for mediation analysis based on the fast-and-robust bootstrap methodology for robust regression estimators, which yields reliable results even when the data deviate from the usual normality assumptions. Various other procedures for mediation analysis are included in package robmed as well. Moreover, robmed introduces a new formula interface that allows to specify mediation models with a single formula, and provides various plots for diagnostics or visual representation of the results.
翻译:在社会、行为和医学科学中,调解模型可以研究独立变量如何通过一个或一个以上的干预变量间接地影响一个依赖变量,这些变量被称为调解人。分析通常通过一系列线性回归进行,间接效应可以作为这些回归系数的产物计算。间接效应的统计意义通常通过基于普通最低平方估计的靴式测试来评估。然而,这一测试对异常或其他与正常假设的偏差十分敏感,这对调解机制理论的实证测试构成了严重威胁。R套套套套件根据快速和粗糙的靴式方法对稳健的回归估计器进行强有力的调解分析程序,即使数据偏离通常的正常假设,也会产生可靠的结果。其他各种调解分析程序也包含在被抢劫的包中。此外,抢劫还引入了一种新的公式界面,能够用单一的公式来指定调解模式,并为结果的诊断或视觉表述提供各种图案。