Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 4 |
Descriptor
| Hypothesis Testing | 6 |
| Meta Analysis | 6 |
| Regression (Statistics) | 6 |
| Effect Size | 4 |
| Models | 3 |
| Simulation | 3 |
| Comparative Analysis | 2 |
| Intervention | 2 |
| Markov Processes | 2 |
| Mathematical Models | 2 |
| Monte Carlo Methods | 2 |
| More ▼ | |
Source
| Society for Research on… | 3 |
| Journal of Educational… | 1 |
| Psychological Review | 1 |
| Research Synthesis Methods | 1 |
Author
Publication Type
| Journal Articles | 3 |
| Reports - Evaluative | 3 |
| Reports - Research | 3 |
| Opinion Papers | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Direct linkJoshi, 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
Download full textTipton, Elizabeth; Pustejovsky, James E. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Descriptors: Randomized Controlled Trials, Sample Size, Effect Size, Hypothesis Testing
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
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
Greenwald, Anthony G.; Rudman, Laurie A.; Nosek, Brian A.; Zayas, Vivian – Psychological Review, 2006
Blanton and Jaccard questioned the 4-test regression method used by Greenwald et al. to test a pure multiplicative theory. The present authors address Blanton and Jaccard's concerns with a combination of simulations and meta-analysis. Simulations show that (a) Blanton and Jaccard's preferred simultaneous regression method has a severe power loss…
Descriptors: Predictor Variables, Regression (Statistics), Theories, Hypothesis Testing
Peer reviewedBecker, Betsy Jane – Journal of Educational Statistics, 1992
Combining information to estimate standardized partial regression coefficients in a linear model is discussed. A combined estimate obtained from the pooled correlation matrix is proposed, and its large sample distribution is obtained. The method is generalized to handle a random effects model in which correlation parameters vary across studies.…
Descriptors: Correlation, Equations (Mathematics), Estimation (Mathematics), Hypothesis Testing
