论文标题
呈现不同效应大小的概率：更好地理解和交流统计不确定性
Presenting the Probabilities of Different Effect Sizes: Towards a Better Understanding and Communication of Statistical Uncertainty
论文作者
论文摘要
社会科学家应该如何理解和传达统计上估计的因果影响的不确定性？我建议我们利用因果效应的后验分布，并提出比不同最小效应大小更大的效果（绝对术语）。概率是对理解和交流的不确定性的直观度量。此外，与常规方法不同，提出的方法不需要不确定性度量或效果大小的决策阈值。我将提出的方法应用于先前的社会科学研究，这表明它可以比原始研究采用的无意义方法更丰富的推论。随附的R软件包使我的方法易于实现。
How should social scientists understand and communicate the uncertainty of statistically estimated causal effects? I propose we utilize the posterior distribution of a causal effect and present the probability of the effect being greater (in absolute terms) than different minimum effect sizes. Probability is an intuitive measure of uncertainty for understanding and communication. In addition, the proposed approach needs no decision threshold for an uncertainty measure or an effect size, unlike the conventional approaches. I apply the proposed approach to a previous social scientific study, showing it enables richer inference than the significance-vs.-insignificance approach taken by the original study. The accompanying R package makes my approach easy to implement.
