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Two-Sample Tests

In: A Primer of Permutation Statistical Methods

Author

Listed:
  • Kenneth J. Berry

    (Colorado State University, Department of Sociology)

  • Janis E. Johnston

    (Alexandria)

  • Paul W. Mielke Jr.

    (Colorado State University, Department of Statistics)

Abstract

This chapter introduces permutation methods for two-sample tests. Included in this chapter are six example analyses illustrating computation of exact permutation probability values for two-sample tests, calculation of measures of effect size for two-sample tests, the effect of extreme values on conventional and permutation two-sample tests, exact and Monte Carlo permutation procedures for two-sample tests, application of permutation methods to two-sample rank-score data, and analysis of two-sample multivariate data. Included in this chapter are permutation versions of Student’s two-sample t test, the Wilcoxon–Mann–Whitney two-sample rank-sum test, Hotelling’s multivariate T 2 test for two independent samples, and a permutation-based alternative for the four conventional measures of effect size for two-sample tests: Cohen’s d ̂ $$\hat{d}$$ , Pearson’s r 2, Kelley’s 𝜖 2, and Hays’ ω ̂ 2 $$\hat{\omega }^{2}$$ .

Suggested Citation

  • Kenneth J. Berry & Janis E. Johnston & Paul W. Mielke Jr., 2019. "Two-Sample Tests," Springer Books, in: A Primer of Permutation Statistical Methods, chapter 0, pages 153-205, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-20933-9_6
    DOI: 10.1007/978-3-030-20933-9_6
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