Journal ArticleDOI
Comparison of the power of the paired samples t test to that of Wilcoxon's signed-ranks test under various population shapes.
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This article is published in Psychological Bulletin.The article was published on 1985-01-01. It has received 113 citations till now. The article focuses on the topics: Wilcoxon signed-rank test & Nonparametric statistics.read more
Citations
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Dominance statistics: Ordinal analyses to answer ordinal questions.
TL;DR: For example, the authors suggests that an ordinal statistic, d, is more robust and equally or more powerful than mean comparisons, and that it is invariant under transformation and conforms more closely to the experimenter's research hypothesis.
Journal ArticleDOI
Treating ordinal scales as interval scales: an attempt to resolve the controversy.
TL;DR: An attempt will be made to sort out the dimensions of the controversy regarding the use of traditional descriptive and inferential statistics for ordinal-level variables, and suggest a possible solution to the problem.
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A more realistic look at the robustness and Type II error properties of the t test to departures from population normality.
TL;DR: The Type I and II error properties of the t test were evaluated by means of a Monte Carlo study that sampled 8 real distribution shapes identified by Micceri (1986, 1989) as being representative of types encountered in psychology and education research.
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Relative Power of the Wilcoxon Test, the Friedman Test, and Repeated-Measures ANOVA on Ranks
TL;DR: In this article, the authors compared the Student t test, the Wilcoxon signed-ranks test, and the sign test for correlated samples from normal, uniform, mixed-normal, exponential, Laplace, and Cauchy distributions.
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Nonparametric Tests of Interaction in Experimental Design
TL;DR: In this article, a review of the use of nonparametric analysis of variance in the design of experiments in the behavioral and social sciences that focused on interaction effects is presented, where the authors show that non-parametric methods lack statistical power and that there is a paucity of techniques in more complicated research designs.
References
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Journal ArticleDOI
Experimental Design: Procedures for the Behavioral Sciences
A. S. Hedayat,Roger E. Kirk +1 more
Book
Foundations of Behavioral Research
Fred N. Kerlinger,Howard B. Lee +1 more
TL;DR: In this article, the authors focus on the relationship between the research problems and the design of the research, and emphasize the fundamentals of understanding how to solve a scientific research problem, focusing upon the relationships between the problems and their solutions.
Book
Experimental Design: Procedures for the Behavioral Sciences
TL;DR: This chapter discusses research strategies and the Control of Nuisance Variables, as well as randomly Randomized Factorial Design with Three or More Treatments and Randomized Block Factorial design, and Confounded Factorial Designs: Designs with Group-Interaction Confounding.
Journal ArticleDOI
Rank Transformations as a Bridge between Parametric and Nonparametric Statistics
TL;DR: Rank as mentioned in this paper is a nonparametric procedure that is applied to the ranks of the data instead of to the data themselves, and it can be viewed as a useful tool for developing non-parametric procedures to solve new problems.
Book
Nonparametrics: Statistical Methods Based on Ranks
TL;DR: Rank Tests for Comparing Two Treatments and Blocked Comparisons for two Treatments in a Population Model and the One-Sample Problem as discussed by the authors were used to compare more than two treatments.