Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…

Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on…

A nonparametric Mokken scale analysis and program is described. Three procedures of scaling (a search procedure, evaluation of the whole set of items as a scale, and extension of an existing scale) provided a coefficient of scalability for all the items together that satisfy the criteria of the Mokken model. (Author/LMO)

A description of a Mokken test program to test the robustness of nonparametric Stochastic scales is presented. For each sample and the whole population, different scale statistics (both on scale and on item level) are computed recursively. A statistic T is presented for testing the robustness of the scales in the samples. (Author)

This paper advocates the use of nonparametric statistics. First, the consequence of using parametric inferential techniques under nonnormality is described. Second, the advantages of using nonparametric techniques are presented. The third purpose is to demonstrate empirically how infrequently nonparametric statistics appear in studies, even those…

Describes the MINISIZE 2 computer program, which permits the user to determine the effect size and the minimum sample size needed so that results of a given analysis will be statistically significant. Explains the program's operation and provides examples. (SLD)

Bootstrap analysis, both for nonparametric statistical inference and for describing sample results stability and replicability, has been gaining prominence among quantitative researchers in educational and psychological research. Procedurally, however, it is often quite a challenge for quantitative researchers to implement bootstrap analysis in…