2014
DOI: 10.1111/ajps.12102
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Arguing for a Negligible Effect

Abstract: 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 eviden… Show more

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Cited by 164 publications
(116 citation statements)
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References 35 publications
(72 reference statements)
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“…This supports our claim that model 4 is both a statistically and substantively null result (Rainey 2014).…”
Section: Shea and Christiansupporting
confidence: 88%
“…This supports our claim that model 4 is both a statistically and substantively null result (Rainey 2014).…”
Section: Shea and Christiansupporting
confidence: 88%
“…This is a positive finding, especially given the expectation that students dropping out of the program do so because of struggles with other coursework, lack of motivation, or general disinterest. However, the result is not statistically significant at traditional levels although a portion of the students who were in the CAC but left do seem to exhibit better attendance [67].…”
Section: Attendance and Disciplinementioning
confidence: 70%
“…The difference between these proportions is indistinguishable from zero, 2 (1)= 0.853, p < .36, two-tailed (Rainey 2014). Specifically, 63% of those respondents who were assigned to interview in Russian agreed with this policy proposal.…”
Section: Placebo Testmentioning
confidence: 85%