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

DOI10.1080/03610918908812791zbMath0695.62121OpenAlexW1969750283MaRDI QIDQ3471458

Abdul R. Habid, Michael R. Harwell

Publication date: 1989

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918908812791

zbMATH Keywords

simulationMultivariate-nonparametric tests

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10)

Related Items (6)

The power method transformation: its probability density function, distribution function, and its further use for fitting data ⋮ A Monte Carlo study of the Friedman test and some competitors in the single factor, repeated measures design with unequal covariances ⋮ An empirical study of five multivariate tests for the single-factor repeated measures model ⋮ Simulating Controlled Variate and Rank Correlations Based on the Power Method Transformation ⋮ A monte carlo study of the friedman and conover tests in the single-factor repeated measures design ⋮ Fast fifth-order polynomial transforms for generating univariate and multivariate nonnormal distributions.

Uses Software

• IMSL Numerical Libraries

Cites Work

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• A method for simulating non-normal distributions
• Simulating multivariate nonnormal distributions
• Practical methods for computing power in testing the multivariate general linear hypothesis
• Sample and population score matrices and sample correlation matrices from an arbitrary population correlation matrix
• Alternative Models for the Analysis of Variance
• A Note on the Generation of Random Normal Deviates
• Rank Transformations as a Bridge Between Parametric and Nonparametric Statistics
• A Tale of Two Regressions
• A power study of a rank transform for the two‐way classification model when interaction may be present
• A Class of Rank Order Tests for a General Linear Hypothesis
• Measures of multivariate skewness and kurtosis with applications

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