Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 4 |
Descriptor
Comparative Analysis | 11 |
Hypothesis Testing | 11 |
Statistical Distributions | 11 |
Sample Size | 5 |
Mathematical Models | 4 |
Statistical Analysis | 4 |
Computer Simulation | 3 |
Equations (Mathematics) | 3 |
Power (Statistics) | 3 |
Probability | 3 |
Chi Square | 2 |
More ▼ |
Source
Applied Psychological… | 1 |
Educational and Psychological… | 1 |
Journal of Educational… | 1 |
Journal of Experimental… | 1 |
Multivariate Behavioral… | 1 |
Practical Assessment,… | 1 |
Psychometrika | 1 |
Author
Publication Type
Journal Articles | 7 |
Reports - Research | 7 |
Reports - Evaluative | 4 |
Speeches/Meeting Papers | 4 |
Information Analyses | 1 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Nordstokke, David W.; Colp, S. Mitchell – Practical Assessment, Research & Evaluation, 2018
Often, when testing for shift in location, researchers will utilize nonparametric statistical tests in place of their parametric counterparts when there is evidence or belief that the assumptions of the parametric test are not met (i.e., normally distributed dependent variables). An underlying and often unattended to assumption of nonparametric…
Descriptors: Nonparametric Statistics, Statistical Analysis, Monte Carlo Methods, Sample Size
Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando – Educational and Psychological Measurement, 2017
We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…
Descriptors: Research Methodology, Hypothesis Testing, Psychology, Social Science Research
Williams, Joseph J.; Griffiths, Thomas L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
Errors in detecting randomness are often explained in terms of biases and misconceptions. We propose and provide evidence for an account that characterizes the contribution of the inherent statistical difficulty of the task. Our account is based on a Bayesian statistical analysis, focusing on the fact that a random process is a special case of…
Descriptors: Experimental Psychology, Bias, Misconceptions, Statistical Analysis
Bennett, Richard P. – 1983
The results of a study of find alternative techniques for testing distributional normality are presented. A group of statistical techniques--some established and some new--were compared using empirical techniques. One new technique which appears to have higher power than the Lilliefors test was subjected to a better definition. Distributions under…
Descriptors: Comparative Analysis, Hypothesis Testing, Power (Statistics), Sample Size
Li, Jianmin; And Others – 1992
This paper discusses the issue of multiple testing and overall Type I error rates in contexts other than multiple comparisons of means. It demonstrates, using a 5 x 5 correlation matrix, the application of 5 recently developed modified Bonferroni procedures developed by the following authors: (1) Y. Hochberg (1988); (2) B. S. Holland and M. D.…
Descriptors: Comparative Analysis, Correlation, Hypothesis Testing, Mathematical Models
Bonett, Douglas G. – Applied Psychological Measurement, 2006
Comparing variability of test scores across alternate forms, test conditions, or subpopulations is a fundamental problem in psychometrics. A confidence interval for a ratio of standard deviations is proposed that performs as well as the classic method with normal distributions and performs dramatically better with nonnormal distributions. A simple…
Descriptors: Intervals, Mathematical Concepts, Comparative Analysis, Psychometrics

Olejnik, Stephen F.; Algina, James – 1984
Five distribution-free alternatives to parametric analysis of covariance (ANCOVA) are presented and demonstrated using a specific data example. The procedures considered are those suggested by Quade (1967); Puri and Sen (1969); McSweeney and Porter (1971); Burnett and Barr (1978); and Shirley (1981). The results of simulation studies investigating…
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Mathematical Formulas

Collins, Linda M.; And Others – Multivariate Behavioral Research, 1993
To assess problems in hypothesis testing and model comparisons based on normed indices caused by latent class models with sparse contingency tables, a simulation was carried out investigating the distributions of the likelihood ratio statistic, the Pearson statistic chi-square, and a new goodness of fit statistic. (SLD)
Descriptors: Chi Square, Comparative Analysis, Computer Simulation, Equations (Mathematics)

Wilcox, Rand R. – Psychometrika, 1993
Modifications are proposed to the recently developed method of comparing one-step M-estimators of location corresponding to two independent groups that provides good control over the probability of Type I error even for unequal sample size, unequal variances, and different shaped distributions. Simulation results reveal cautions required. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Equations (Mathematics), Estimation (Mathematics)
Reshetar, Rosemary A.; Swaminathan, Hariharan – 1992
This study compared the model of J. E. Grizzle, C. F. Starmer, and G. G. Koch (GSK, 1969) and log-linear model-based approaches for testing hypotheses in r x c contingency tables. Tables were simulated under various conditions of table, sample, row-effect size, and column-effect size. Test statistics for column (main) and interaction effects were…
Descriptors: Chi Square, Classification, Comparative Analysis, Effect Size

Wilcox, Rand R.; Charlin, Ventura L. – Journal of Educational Statistics, 1986
This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)
Descriptors: Comparative Analysis, Computer Simulation, Computer Software, Equations (Mathematics)