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AI 根据所提供的论文材料归类:论文直接研究中介效应检验,属于因果分析相关推断,但摘要未交代因果解释所需条件。

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关注这篇论文的作者
Grant Hillier

中介效应的改进检验

研究问题
在干扰参数使中介效应检验的功效随参数位置显著变化时,能否改造似然比检验,同时改善检验水平控制与功效表现?
方法与思路
作者提出扩大似然比检验的拒绝域,先构造特定显著性水平下渐近精确的检验,再设计更简单、近似精确的拒绝域族。
材料陈述的贡献
摘要称,新检验改善了原有检验的表现,并提供实施及计算 p 值的表格;模拟考察了非高斯、异方差和 logit 情形。
阅读关注点
应核对中介效应的模型设定、干扰参数范围、渐近精确的定义,以及拒绝域扩展如何影响水平控制、功效和 p 值计算。
阅读边界
这是 arXiv 预印本,同行评审及期刊接收未核实;摘要未说明完整假设,模拟结果也不能证明任意模型下均有效。

原文摘要

Testing for a mediation effect is important in many disciplines, but is made difficult - even asymptotically - by the influence of nuisance parameters. Classical tests such as likelihood ratio (LR) and Wald (Sobel) tests have very poor power properties in parts of the parameter space, and many attempts have been made to produce improved tests, with limited success. In this paper we show that augmenting the critical region of the LR test can produce a test with much improved behavior everywhere. In fact, we first show that there exists a test of this type that is (asymptotically) exact for certain test levels $α$, including the common choices $α=.01,.05,.10.$ The critical region of this exact test has some undesirable properties. We go on to show that there is a very simple class of augmented LR critical regions which provides tests that are nearly exact, and avoid the issues inherent in the exact test. We suggest an optimal and coherent member of this class, provide the table needed to implement the test and to report p-values if desired. Simulation confirms validity with non-Gaussian disturbances, under heteroskedasticity, and in a nonlinear (logit) model. A short application of the method to an entrepreneurial attitudes study is included for illustration.

笔记与分组