A Monte Carlo study of the Friedman test and some competitors in the single factor, repeated measures design with unequal covariances
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Publication:1361556
DOI10.1016/0167-9473(92)00060-5zbMath0937.62523OpenAlexW1980465329MaRDI QIDQ1361556
Ronald C. Serlin, Michael R. Harwell
Publication date: 25 August 1997
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0167-9473(92)00060-5
Related Items (5)
An improved mixed-homogeneously weighted moving average-CUSUM control chart for efficient monitoring of a process mean ⋮ ANOVA with binary variables: the F-test and some alternatives ⋮ Comparison of aligned Friedman rank and parametric methods for testing interactions in split-plot designs ⋮ The Effects of Misconceptions on the Properties of Friedman's Test ⋮ A monte carlo study of the friedman and conover tests in the single-factor repeated measures design
Cites Work
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- A method for simulating non-normal distributions
- Using Weighted Rankings in the Analysis of Complete Blocks with Additive Block Effects
- A Note on the Generation of Random Normal Deviates
- An empirical study of the type I error rate and power for some selected normal-theory and nonparametric tests of the independence of two sets of variables
- The Rank Transform Method in Some Two-Factor Designs
- Comparison of Asymptotically Distribution-Free Procedures for the Analysis of Complete Blocks
- Tests based on weighted rankings in complete blocks: exact distribution and monte carlo simulation
- Linear Models with Exchangeably Distributed Errors
- Approximations of the critical region of the fbietkan statistic
- Rank Transformations as a Bridge Between Parametric and Nonparametric Statistics
- Multi-Dimensional Extensions of the Chebyshev Polynomials
- The Problem of $m$ Rankings
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