Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 2 |
Descriptor
Correlation | 4 |
Nonparametric Statistics | 4 |
Computer Programs | 2 |
Effect Size | 2 |
Analysis of Covariance | 1 |
Computer Software | 1 |
Data | 1 |
Data Analysis | 1 |
Evaluation Methods | 1 |
Mathematical Concepts | 1 |
Matrices | 1 |
More ▼ |
Publication Type
Journal Articles | 4 |
Reports - Descriptive | 4 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
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…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation
Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2010
Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests (e.g., multiple regression, ANOVA) can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric…
Descriptors: Social Sciences, Regression (Statistics), Nonparametric Statistics, Data

Divgi, D. R. – Psychometrika, 1979
A new computer subroutine has been developed for calculating the tetrachoric correlation coefficient. Recent advances in computing inverse normal and bivariate normal distributions have been utilized. The procedure is useful for item analysis. (Author/JKS)
Descriptors: Computer Programs, Correlation, Nonparametric Statistics, Program Descriptions

Steiger, James H. – Educational and Psychological Measurement, 1979
The program presented computes a chi-square statistic for testing pattern hypotheses on correlation matrices. The statistic is based on a multivariate generalization of the Fisher r-to-z transformation. This statistic has small sample performance which is superior to an analogous likelihood ratio statistic obtained via the analysis of covariance…
Descriptors: Analysis of Covariance, Computer Programs, Correlation, Matrices