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Beyond Flimsy Assertions: A Better Way to Show Variables Have No Political Impact
Insights from the Field
statistical significance
confidence intervals
negligible effect
Methodology
AJPS
9 text files
1 datasets
Dataverse
Arguing for a Negligible Effect was authored by Carlisle Rainey. It was published by Wiley in AJPS in 2014.

Political scientists often claim variables have no effect when coefficients aren't statistically significant. This article introduces researchers to more robust methods, such as 90% confidence intervals, for demonstrating negligible impacts and supporting their hypotheses with stronger evidence.

Key Concept: Statistical Significance vs. Practical Negligibility

The common approach of relying solely on p-values (especially the default cutoff) is insufficient for proving true negligibility.

New Approach: Using 90% Confidence Intervals

Instead, researchers can employ narrower confidence intervals like the 90%, providing more compelling evidence that effects are genuinely small or zero.

Supporting Examples: Illustrative Cases

Several examples demonstrate how shifting from reliance on weak statistical tests to these stronger interval-based methods clarifies findings and strengthens arguments for negligible political influence.

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American Journal of Political Science
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