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Direct linkMara, Constance A.; Cribbie, Robert A. – Journal of Experimental Education, 2018
Researchers are often interested in establishing equivalence of population variances. Traditional difference-based procedures are appropriate to answer questions about differences in some statistic (e.g., variances, etc.). However, if a researcher is interested in evaluating the equivalence of population variances, it is more appropriate to use a…
Descriptors: Statistical Analysis, Differences, Comparative Analysis, Research Problems
Download full textWilhelm, Anne Garrison; Gillespie Rouse, Amy; Jones, Francesca – Practical Assessment, Research & Evaluation, 2018
Although inter-rater reliability is an important aspect of using observational instruments, it has received little theoretical attention. In this article, we offer some guidance for practitioners and consumers of classroom observations so that they can make decisions about inter-rater reliability, both for study design and in the reporting of data…
Descriptors: Interrater Reliability, Measurement, Observation, Educational Research
Pedersen, Ellen Raben; Juhl, Peter Møller – Journal of Speech, Language, and Hearing Research, 2017
Purpose: Critical differences state by how much 2 test results have to differ in order to be significantly different. Critical differences for discrimination scores have been available for several decades, but they do not exist for speech reception thresholds (SRTs). This study presents and discusses how critical differences for SRTs can be…
Descriptors: Speech, Simulation, Differences, Test Results
Kang, Yoonjeong; Harring, Jeffrey R.; Li, Ming – Journal of Experimental Education, 2015
The authors performed a Monte Carlo simulation to empirically investigate the robustness and power of 4 methods in testing mean differences for 2 independent groups under conditions in which 2 populations may not demonstrate the same pattern of nonnormality. The approaches considered were the t test, Wilcoxon rank-sum test, Welch-James test with…
Descriptors: Comparative Analysis, Monte Carlo Methods, Statistical Analysis, Robustness (Statistics)
McNeish, Daniel M. – Journal of Educational and Behavioral Statistics, 2016
Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…
Descriptors: Models, Statistical Analysis, Hierarchical Linear Modeling, Sample Size
Hummel, Thomas J.; Johnston, Charles B. – 1986
This study investigated seven methods for analyzing multivariate group differences. Bonferroni t statistics, multivariate analysis of variance (MANOVA) followed by analysis of variance (ANOVA), and five other methods were studied using Monte Carlo methods. Methods were compared with respect to (1) experimentwise error rate; (2) power; (3) number…
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, Differences
