Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 5 |
Descriptor
Bayesian Statistics | 5 |
Effect Size | 5 |
Randomized Controlled Trials | 5 |
Educational Research | 3 |
Foreign Countries | 2 |
Intervention | 2 |
Probability | 2 |
Program Effectiveness | 2 |
Sample Size | 2 |
Statistical Distributions | 2 |
Accuracy | 1 |
More ▼ |
Source
Educational Researcher | 1 |
Educational and Psychological… | 1 |
International Journal of… | 1 |
Journal of Experimental… | 1 |
Society for Research on… | 1 |
Author
Higgins, Steve | 2 |
Kasim, Adetayo | 2 |
Singh, Akansha | 2 |
Uwimpuhwe, Germaine | 2 |
Coux, Mickael | 1 |
Hok Chio Lai | 1 |
Kamata, Akihito | 1 |
Li, Ji | 1 |
Liang, Xinya | 1 |
Shkedy, Ziv | 1 |
Simpson, Adrian | 1 |
More ▼ |
Publication Type
Journal Articles | 4 |
Reports - Research | 4 |
Reports - Evaluative | 1 |
Education Level
Elementary Education | 1 |
Elementary Secondary Education | 1 |
Grade 7 | 1 |
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Location
United Kingdom (England) | 2 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Winnie Wing-Yee Tse; Hok Chio Lai – Society for Research on Educational Effectiveness, 2021
Background: Power analysis and sample size planning are key components in designing cluster randomized trials (CRTs), a common study design to test treatment effect by randomizing clusters or groups of individuals. Sample size determination in two-level CRTs requires knowledge of more than one design parameter, such as the effect size and the…
Descriptors: Sample Size, Bayesian Statistics, Randomized Controlled Trials, Research Design
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Kasim, Adetayo – International Journal of Research & Method in Education, 2021
Educational researchers advocate the use of an effect size and its confidence interval to assess the effectiveness of interventions instead of relying on a p-value, which has been blamed for lack of reproducibility of research findings and the misuse of statistics. The aim of this study is to provide a framework, which can provide direct evidence…
Descriptors: Educational Research, Randomized Controlled Trials, Bayesian Statistics, Effect Size
Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
Simpson, Adrian – Educational Researcher, 2019
A recent paper uses Bayes factors to argue a large minority of rigorous, large-scale education RCTs are "uninformative." The definition of "uninformative" depends on the authors' hypothesis choices for calculating Bayes factors. These arguably overadjust for effect size inflation and involve a fixed prior distribution,…
Descriptors: Randomized Controlled Trials, Bayesian Statistics, Educational Research, Program Evaluation
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Coux, Mickael; Xiao, ZhiMin; Shkedy, Ziv; Kasim, Adetayo – Journal of Experimental Education, 2022
Educational stakeholders are keen to know the magnitude and importance of different interventions. However, the way evidence is communicated to support understanding of the effectiveness of an intervention is controversial. Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This…
Descriptors: Program Effectiveness, Intervention, Multivariate Analysis, Bayesian Statistics