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Full-Text Articles in Applied Statistics
You Think You’Ve Got Trivials?, Shlomo S. Sawilowsky
You Think You’Ve Got Trivials?, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Effect sizes are important for power analysis and meta-analysis. This has led to a debate on reporting effect sizes for studies that are not statistically significant. Contrary and supportive evidence has been offered on the basis of Monte Carlo methods. In this article, clarifications are given regarding what should be simulated to determine the possible effects of piecemeal publishing trivial effect sizes.
Fast Permutation Tests That Maximize Power Under Conventional Monte Carlo Sampling For Pairwise And Multiple Comparisons, J. D. Opdyke
Fast Permutation Tests That Maximize Power Under Conventional Monte Carlo Sampling For Pairwise And Multiple Comparisons, J. D. Opdyke
Journal of Modern Applied Statistical Methods
While the distribution-free nature of permutation tests makes them the most appropriate method for hypothesis testing under a wide range of conditions, their computational demands can be runtime prohibitive, especially if samples are not very small and/or many tests must be conducted (e.g. all pairwise comparisons). This paper presents statistical code that performs continuous-data permutation tests under such conditions very quickly often more than an order of magnitude faster than widely available commercial alternatives when many tests must be performed and some of the sample pairs contain a large sample. Also presented is an efficient method for obtaining a …