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Shunji Wang; Katerina M. Marcoulides; Jiashan Tang; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…
Descriptors: Hypothesis Testing, Error of Measurement, Comparative Analysis, Monte Carlo Methods
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
Spencer, Bryden – ProQuest LLC, 2016
Value-added models are a class of growth models used in education to assign responsibility for student growth to teachers or schools. For value-added models to be used fairly, sufficient statistical precision is necessary for accurate teacher classification. Previous research indicated precision below practical limits. An alternative approach has…
Descriptors: Monte Carlo Methods, Comparative Analysis, Accuracy, High Stakes Tests
Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon; Penfield, Randall D. – Educational and Psychological Measurement, 2013
The Rasch model, a member of a larger group of models within item response theory, is widely used in empirical studies. Detection of uniform differential item functioning (DIF) within the Rasch model typically employs null hypothesis testing with a concomitant consideration of effect size (e.g., signed area [SA]). Parametric equivalence between…
Descriptors: Test Bias, Effect Size, Item Response Theory, Comparative Analysis
Society for Research on Educational Effectiveness, 2013
One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…
Descriptors: Research Design, Effect Size, Intervention, Statistical Analysis
Itang'ata, Mukaria J. J. – ProQuest LLC, 2013
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Descriptors: Comparative Analysis, Probability, Statistical Bias, Monte Carlo Methods
Espelage, Dorothy L.; Rose, Chad A.; Polanin, Joshua R. – Remedial and Special Education, 2016
This 3-year study evaluated the effectiveness of the Second Step-Student Success Through Prevention (SS-SSTP) social-emotional learning program on increasing prosocial behaviors that could serve as protective factors against peer conflict and bullying among students with disabilities. Participants included 123 students with disabilities across 12…
Descriptors: Longitudinal Studies, Prosocial Behavior, Academic Ability, Middle School Students
Swaminathan, Hariharan; Horner, Robert H.; Rogers, H. Jane; Sugai, George – Society for Research on Educational Effectiveness, 2012
This study is aimed at addressing the criticisms that have been leveled at the currently available statistical procedures for analyzing single subject designs (SSD). One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been…
Descriptors: Evidence, Effect Size, Research Methodology, Intervention
Klockars, Alan J.; Hancock, Gregory R. – 1990
Two strategies, derived from J. P. Schaffer (1986), were compared as tests of significance for a complete set of planned orthogonal contrasts. The procedures both maintain an experimentwise error rate at or below alpha, but differ in the manner in which they test the contrast with the largest observed difference. One approach proceeds directly to…
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Methodology

Mendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1974
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Design

Quintana, Stephen M.; Maxwell, Scott E. – Journal of Educational Statistics, 1994
Seven univariate procedures for testing omnibus null hypotheses for data gathered from repeated measures designs were evaluated, comparing five alternative approaches with two more traditional procedures. Results suggest that the alternatives are improvements. The most effective alternate procedure in controlling Type I error rates is discussed.…
Descriptors: Comparative Analysis, Hypothesis Testing, Monte Carlo Methods, Research Methodology
Finch, W. Holmes; French, Brian F. – Educational and Psychological Measurement, 2007
Differential item functioning (DIF) continues to receive attention both in applied and methodological studies. Because DIF can be an indicator of irrelevant variance that can influence test scores, continuing to evaluate and improve the accuracy of detection methods is an essential step in gathering score validity evidence. Methods for detecting…
Descriptors: Item Response Theory, Factor Analysis, Test Bias, Comparative Analysis
Klockars, Alan J.; Hancock, Gregory R. – 1993
The challenge of multiple comparisons is to maximize the power for answering specific research questions, while still maintaining control over the rate of Type I error. Several multiple comparison procedures have been suggested to meet this challenge. The stagewise protected procedure (SPP) of A. J. Klockars and G. R. Hancock tests null hypotheses…
Descriptors: Comparative Analysis, Computer Simulation, Hypothesis Testing, Mathematical Models

Clinch, Jennifer J.; Keselman, H. J. – Journal of Educational Statistics, 1982
The analysis of variance, Welch, and Brown and Forsyth tests for mean equality were compared using Monte Carlo methods. The tests' rates of Type I error and power were examined when populations were nonnormal, variances were heterogeneous, and group sizes were unequal. Recommendations for use are presented. (Author/JKS)
Descriptors: Analysis of Variance, Comparative Analysis, Data Analysis, Hypothesis Testing

Wilson, Gale A.; Martin, Samuel A. – Educational and Psychological Measurement, 1983
Either Bartlett's chi-square test of sphericity or Steiger's chi-square test can be used to test the significance of a correlation matrix to determine the appropriateness of factor analysis. They were evaluated using computer-generated correlation matrices. Steiger's test is recommended due to its increased power and computational simplicity.…
Descriptors: Comparative Analysis, Correlation, Factor Analysis, Hypothesis Testing
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