Political scientists often theorize that an explanatory variable should have “no effect” and support this claim by demonstrating that its coefficient's estimate is not statistically significant. This empirical argument is quite weak, but I introduce applied researchers to simple, powerful tools that can strengthen their arguments for this hypothesis. With several supporting examples, I illustrate that researchers can use 90% confidence intervals to argue against meaningful effects and provide persuasive evidence for their hypothesis.
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