Testing for homogeneity in a general one-way classification with fixed effects: power simulations and comparative study

DOI10.1016/S0167-9473(02)00264-5zbMath1429.62232OpenAlexW2108751141MaRDI QIDQ956800

Doğan Argaç

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(02)00264-5

zbMATH Keywords

mean equalitypower of testsgeneralized Behrens-Fisher problemheteroscedastic variances

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Parametric hypothesis testing (62F03) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (2)

Testing equality of correlation coefficients in two populations via permutation methods ⋮ Testing hypotheses on coefficients of variation from a series of two-armed experiments

Cites Work

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• A closer examination on some parametric alternatives to the ANOVA \(F\)-test
• Small sample properties of tests on homogeneity in one-way anova and meta-analysis
• Approximations to permutation distributions in the completely randomized design
• Controversies in the Foundations of Statistics
• Size performance of some tests in one-way anova
• Improving the brown-forsythe solution to the generalized behrens-fisher problem
• The 'improved' brown and forsythe test for mean equality: some things can't be fixed
• The Fisher‐Pitman permutation test: A non‐robust alternative to the normal theory F test when variances are heterogeneous
• One-way analysis of variance with unequal variances.
• The Small Sample Behavior of Some Statistics Which Test the Equality of Several Means
• Two-way fixed effects analysis of variance when the error variances may be unequal
• THE COMPARISON OF SEVERAL GROUPS OF OBSERVATIONS WHEN THE RATIOS OF THE POPULATION VARIANCES ARE UNKNOWN
• ON THE COMPARISON OF SEVERAL MEAN VALUES: AN ALTERNATIVE APPROACH
• Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, I. Effect of Inequality of Variance in the One-Way Classification

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