In psychological research，researchers may need to provide evidence for the non-existence of effects（i. e.，nil effect）. However，the most widely used statistical inference framework in psychology，the null hypothesis significance test （NHST），cannot provide evidence for nil effects. In other words，a non-significant p-value（e.g.，p>0.05）cannot be interpreted as evidence that supports the nil hypothesis. As a re sult，in practice，researchers either avoid interpreting the non-significant results，or mis-interpret the non-significant results as evidence for the nil hypothesis. Here we introduced three methods that can evaluate nil effects，the equivalence test，Bayesian estimation，and Bayesian factor（BF），to Chinese researchers. We illustrated how to apply these methods to real psychological data using two open datasets. This primer may help Chinese researchers to improve their statistical inference for non-significant results.

在心理学研究中，研究者可能需要评估效应是否不存在，但常用的原假设显著性检验无法提供支持零效应的证据。因此，实践中研究者要么对p>0.05的情况进行回避，要么错误地认为p>0.05支持了原假设。近年来，等价检验、贝叶斯估计和贝叶斯因子逐渐被用于评估零效应。文章介绍了这三种方法的原理，并通过两个实例分析，展示三种方法的实际应用。这三种评估零效应的方法能够帮助心理学研究者在实际研究中进行合理的统计推断和研究决策。