Randomized Designs: Interval Data

Kenneth J. Berry, Paul W. Mielke and Janis E. Johnston
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Kenneth J. Berry: Colorado State University, Department of Sociology
Paul W. Mielke: Colorado State University, Department of Statistics
Janis E. Johnston: U.S. Government

Chapter 3 in Permutation Statistical Methods, 2016, pp 57-113 from Springer

Abstract: Abstract Chapter 3 utilizes the Multi-Response Permutation Procedures (MRPP) presented in Chap. 2 to develop the relationships between the test statistics of MRPP, δ and $$\mathfrak{R}$$ , and selected conventional tests and measures designed for the analysis of completely randomized data at the interval level of measurement. The structure of the MRPP test statistic, δ, depends on the choice of v in the generalized Minkowski distance function and the treatment-group weights, C i , i = 1, …, g. Four tests are examined in this chapter: (1) Student’s two-sample t test with interval-level univariate response measurements, (2) Hotelling’s two-sample T 2 test with multivariate interval-level response measurements, (3) one-way fixed-effects analysis of variance (ANOVA) with interval-level univariate response measurements, and (4) one-way multivariate analysis of variance (MANOVA) with interval-level multivariate response measurements.

Keywords: Exact Probability; Trace Test; Permutation Method; Population Standard Deviation; Permutation Model (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-28770-6_3

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DOI: 10.1007/978-3-319-28770-6_3

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