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Distcomp: Comparing distributions

David M. Kaplan

arXiv 5 Oct 2021 · Statistics — Computation

arXiv:2110.02327 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The distcomp command is introduced and illustrated. The command assesses whether or not two distributions differ at each possible value while controlling the probability of any false positive, even in finite samples. Syntax and the underlying methodology (from Goldman and Kaplan, 2018) are discussed. Multiple examples illustrate the distcomp command, including revisiting the experimental data of Gneezy and List (2006) and the regression discontinuity design of Cattaneo, Frandsen, and Titiunik (2015).

Citation extraction

8
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29
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distinct cited
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Goldman, M., and D. M. Kaplan (2018) Comparing distributions by multiple testing across quantiles or CDF values1.000136100%
2Gneezy, U., and J. A. List (2006) Putting Behavioral Economics to Work: Testing for Gift Exchange in Labor Markets Using Field Experiments1.00053100%
3Cattaneo, M. D., B. R. Frandsen, and R. Titiunik (2015) Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate0.92843100%
4Buja, A., and W. Rolke (2006) Calibration for Simultaneity: (Re)Sampling Methods for Simultaneous Inference with Applications to Function Estimation and Funct…0.84333100%
5Atkinson, A. B (1987) On the Measurement of Poverty0.40511100%
6Eicker, F (1979) The asymptotic distribution of the suprema of the standardized empirical processes0.40511100%
7Lehmann, E. L., and J. P. Romano (2005) Testing Statistical Hypotheses0.40511100%
8Wilks, S. S (1962) Mathematical Statistics0.40511100%

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Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Inference on Consensus Ranking of Distributions0.40511