每周论坛 | Insufficient Statistical Power of Chi-square Model

报告人：柯紫筠 副教授

报告人单位：中山大学心理学系

题目：Insufficient Statistical Power of the Chi-square Model Fit Test for the Exclusion Assumption of the Instrumental Variable Method

时间：2023年11月13日（周一）14:20-16:00

地点：心理学系305

报告简介

Regression estimates are biased when confounders are omitted or when there are other similar risks to validity. The instrumental variable (IV) method can be used instead to obtain less biased estimates or to strengthen the causal inferences. One key assumption critical to the validity of the IV method is the exclusion assumption, which requires instruments to be correlated with the outcome variable only through endogenous predictors. The chi-square test of model fit is widely used as a diagnostic test for this assumption. Previous simulation studies assessed the power of this diagnostic test only in situations with strong exclusion assumption violation. However, low to moderate levels of assumption violation are not uncommon in reality, especially when the exclusion assumption is violated indirectly. In this study, we showed through Monte Carlo simulations that the chi-square model fit test suffered from a severe lack of power (< 30%) to detect violations of the exclusion assumption when the level of violation was of typical size, and the IV causal inferences were inaccurate and misleading in this case. We thus advise using the IV method with caution unless there is a chance for thorough assumption diagnostics, like in meta-analyses or experiments.

报告人简介

柯紫筠，中山大学心理学系副教授，硕士生导师。长期从事计量心理学研究，主要研究方向包括元分析技术的改进、非实验研究中的因果推断、贝叶斯方法以及认知建模。主持和参与多项国家级和省部级项目。以主要作者在《Psychological Methods》等心理学主流国际高水平期刊发表论文10余篇。