Publication Date
In 2025 | 0 |
Since 2024 | 3 |
Since 2021 (last 5 years) | 7 |
Descriptor
Error of Measurement | 7 |
Hypothesis Testing | 7 |
Simulation | 5 |
Evaluation Methods | 3 |
Comparative Analysis | 2 |
Effect Size | 2 |
Statistical Analysis | 2 |
Statistical Inference | 2 |
Accuracy | 1 |
Adaptive Testing | 1 |
Bayesian Statistics | 1 |
More ▼ |
Source
Society for Research on… | 2 |
Educational and Psychological… | 1 |
Journal of Educational… | 1 |
National Center for Education… | 1 |
Research Synthesis Methods | 1 |
Structural Equation Modeling:… | 1 |
Author
Beretvas, S. Natasha | 1 |
Cooperman, Allison W. | 1 |
Deke, John | 1 |
Finucane, Mariel | 1 |
Jeffry White | 1 |
Jiashan Tang | 1 |
Joshi, Megha | 1 |
Katerina M. Marcoulides | 1 |
Ke-Hai Yuan | 1 |
Kristen Hunter | 1 |
Kristin Porter | 1 |
More ▼ |
Publication Type
Reports - Research | 6 |
Journal Articles | 4 |
Guides - Non-Classroom | 1 |
Education Level
High Schools | 1 |
Higher Education | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Researchers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
SAT (College Admission Test) | 1 |
What Works Clearinghouse Rating
Steffen Erickson – Society for Research on Educational Effectiveness, 2024
Background: Structural Equation Modeling (SEM) is a powerful and broadly utilized statistical framework. Researchers employ these models to dissect relationships into direct, indirect, and total effects (Bollen, 1989). These models unpack the "black box" issues within cause-and-effect studies by examining the underlying theoretical…
Descriptors: Structural Equation Models, Causal Models, Research Methodology, Error of Measurement
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
Cooperman, Allison W.; Weiss, David J.; Wang, Chun – Educational and Psychological Measurement, 2022
Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests--a Z test, likelihood ratio test, and score ratio index--have demonstrated desirable statistical properties in this context, including low false positive rates and high…
Descriptors: Error of Measurement, Psychometrics, Hypothesis Testing, Simulation
Joshi, Megha; Pustejovsky, James E.; Beretvas, S. Natasha – Research Synthesis Methods, 2022
The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some…
Descriptors: Meta Analysis, Regression (Statistics), Models, Effect Size
Kristin Porter; Luke Miratrix; Kristen Hunter – Society for Research on Educational Effectiveness, 2021
Background: Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs)…
Descriptors: Statistical Analysis, Hypothesis Testing, Computer Software, Randomized Controlled Trials
Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Jeffry White – Journal of Educational Research and Practice, 2024
Violations of normality and homogeneity are common in educational data. When this occurs, the use of parametric statistics may be inappropriate. A generalized form of nonparametric analyses based on the Puri and Sen L statistic provides an alternative approach. Using a chi-square distribution, this technique is easy to apply and has significant…
Descriptors: Nonparametric Statistics, Learning Analytics, Evaluation Methods, Guidance