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Combination of distribution-free tests for the general two-sample problem with application to the social sciences

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  • Marco Marozzi

Abstract

The problem of detecting any differences between the distributions of two populations is addressed within the non parametric permutation framework of combined tests. Combined testing has been very useful to address the location, the scale, and the location/scale problems. The aim of the paper is to see whether combined testing is useful also for the general two-sample problem. The framework of combined testing for the general two-sample problem is presented and some tests are proposed. These tests are valid even when a non random sample of units is randomized into two groups. Type 1 error rate and power characteristics of the new tests are investigated and compared to former tests. It is shown that the new tests compare favorably with the former ones. An application to a very important socioeconomic problem is discussed.

Suggested Citation

  • Marco Marozzi, 2016. "Combination of distribution-free tests for the general two-sample problem with application to the social sciences," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(21), pages 6421-6435, November.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:21:p:6421-6435
    DOI: 10.1080/03610926.2014.919398
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    Cited by:

    1. Massimiliano Giacalone & Agata Zirilli & Mariacarla Moleti & Angela Alibrandi, 2018. "Does the iodized salt therapy of pregnant mothers increase the children IQ? Empirical evidence of a statistical study based on permutation tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(3), pages 1423-1435, May.

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