论文标题
关于由于外部有效性有限而导致因果推断无效的概率
On the probability of invalidating a causal inference due to limited external validity
论文作者
论文摘要
在实证研究中，外部有效性通常值得怀疑，尤其是由于内部有效性和外部有效性之间的权衡而导致的随机实验。为了量化外部有效性的鲁棒性，必须首先概念化完全代表目标人群（即理想样本）和观察到的样本的样本之间的差距。借助Frank＆Min（2007）和Frank等人。 （2013年），我将这种差距定义为未观察到的样本，并打算在本研究中量化其与原假设统计检验（NHST）的关系。由于外部有效性有限，即PEV引起的因果推断的可能性是未能基于理想样本拒绝零假设的概率，只要根据观察到的样本拒绝了零假设。这项研究说明了通过经验示例评估PEV外部有效性的指南和程序（即Borman等人（2008））。具体而言，人们将能够找到未观察到的样本统计量的阈值，该样本统计量将使PEV高于所需的值，并使用此信息来表征未观察到的样本，从而使研究的外部有效性降低了鲁棒。当认为NHST基于理想样本时，PEV被证明与统计能力有关。
External validity is often questionable in empirical research, especially in randomized experiments due to the trade-off between internal validity and external validity. To quantify the robustness of external validity, one must first conceptualize the gap between a sample that is fully representative of the target population (i.e., the ideal sample) and the observed sample. Drawing on Frank & Min (2007) and Frank et al. (2013), I define such gap as the unobserved sample and intend to quantify its relationship with the null hypothesis statistical testing (NHST) in this study. The probability of invalidating a causal inference due to limited external validity, i.e., the PEV, is the probability of failing to reject the null hypothesis based on the ideal sample provided the null hypothesis has been rejected based on the observed sample. This study illustrates the guideline and the procedure of evaluating external validity with the PEV through an empirical example (i.e., Borman et al. (2008)). Specifically, one would be able to locate the threshold of the unobserved sample statistic that would make the PEV higher than a desired value and use this information to characterize the unobserved sample that would render external validity of the research in question less robust. The PEV is shown to be linked to statistical power when the NHST is thought to be based on the ideal sample.
