It is often claimed that only experiments can support strong causal inferences and therefore they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments results in their overuse both by researchers and decision makers and in an underappreciation of their shortcomings. Neglect of other methods often follows. Experiments can suggest whether X causes Y in a specific experimental setting; however, they often fail to elucidate either the mechanisms responsible for an effect or the strength of an effect in everyday natural settings. In this article, we consider two overarching issues. First, experiments have important limitations. We highlight problems with external, construct, statistical-conclusion, and internal validity; replicability; and conceptual issues associated with simple X causes Y thinking. Second, quasi-experimental and nonexperimental methods are absolutely essential. As well as themselves estimating causal effects, these other methods can provide information and understanding that goes beyond that provided by experiments. A research program progresses best when experiments are not treated as privileged but instead are combined with these other methods.

人们经常声称只有实验才能支持强有力的因果推理，因此它们应该在行为科学中享有特权。我们不同意。高估实验会导致研究人员和决策者过度使用它们，并低估它们的缺点。其他方法的忽视往往随之而来。实验可以表明X是否导致Y在特定的实验环境中；然而，他们往往无法阐明在日常自然环境中产生影响的机制或影响的强度。在本文中，我们考虑两个首要问题。首先，实验有重要的局限性。我们强调外部有效性、结构有效性、统计结论有效性和内部有效性的问题；可复制性；与简单X相关的概念问题导致Y思维。其次，准实验和非实验方法是绝对必要的。除了它们自己估计因果效应之外，这些其他方法还可以提供超出实验提供的信息和理解。当实验不被视为特权，而是与这些其他方法相结合时，研究计划的进展最好。