Graham Elliott, Nikolay Kudrin, Kaspar Wüthrich
arXiv 16 May 2022 · Econometrics · publishedThe Review of Economics and Statistics (2025) · 1 citations (OpenAlex)
arXiv:2205.07950 · PDF · DOI · OpenAlex · Extracted main text
A flourishing empirical literature investigates the prevalence of $p$-hacking based on the distribution of $p$-values across studies. Interpreting results in this literature requires a careful understanding of the power of methods for detecting $p$-hacking. We theoretically study the implications of likely forms of $p$-hacking on the distribution of $p$-values to understand the power of tests for detecting it. Power can be low and depends crucially on the $p$-hacking strategy and the distribution of true effects. Combined tests for upper bounds and monotonicity and tests for continuity of the $p$-curve tend to have the highest power for detecting $p$-hacking.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Brodeur, A., Cook, N., and Heyes, A (2020) Methods matter: p-hacking and publication bias in causal analysis in economics | 1.000 | 10 | 5 | 100% |
| 2 | Simonsohn, U., Nelson, L. D., and Simmons, J. P (2014) P-curve: a key to the file-drawer | 1.000 | 7 | 4 | 100% |
| 3 | Elliott, G., Kudrin, N., and Wüthrich, K (2022) Detecting p-hacking self | 0.947 | 20 | 8 | 85% |
| 4 | Cox, G. and Shi, X (2022) Simple Adaptive Size-Exact Testing for Full-Vector and Subvector Inference in Moment Inequality Models | 0.874 | 5 | 2 | 100% |
| 5 | Brodeur, A., Cook, N., and Heyes, A (2022) Methods matter: P-hacking and publication bias in causal analysis in economics | 0.737 | 3 | 2 | 100% |
| 6 | Cattaneo, M. D., Jansson, M., and Ma, X (2020) Simple local polynomial density estimators | 0.737 | 3 | 2 | 100% |
| 7 | Head, M. L., Holman, L., Lanfear, R., Kahn, A. T., and Jennions, M. D (2015) The extent and consequences of p-hacking in science | 0.737 | 3 | 2 | 100% |
| 8 | Kudrin, N (2024) Testing for and evaluating the extent of selective reporting self | 0.737 | 3 | 2 | 100% |
| 9 | Andrews, I. and Kasy, M (2019) Identification of and correction for publication bias | 0.644 | 2 | 2 | 100% |
| 10 | Beare, B. K. and Moon, J.-M (2015) Nonparametric tests of density ratio ordering | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 57 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | When is $p$-hacking detectable? | 0.928 | 4 | 3 |
| 2 | Literature Review and Evidence Aggregation: a Toolkit for Applied Micro | 0.843 | 4 | 3 |