Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 3 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Comparative Analysis | 3 |
| Probability | 3 |
| Research Problems | 3 |
| Models | 2 |
| Adolescents | 1 |
| Algorithms | 1 |
| Bayesian Statistics | 1 |
| Case Studies | 1 |
| Compliance (Psychology) | 1 |
| Computation | 1 |
| Correlation | 1 |
| More ▼ | |
Author
| Brian Keller | 1 |
| Craig Enders | 1 |
| Duxbury, Scott W. | 1 |
| Egamaria Alacam | 1 |
| Han Du | 1 |
| Hardy, Jessica K. | 1 |
| Landrum, Timothy | 1 |
| McLeod, Ragan H. | 1 |
| Sweigart, Chris A. | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
| Reports - Evaluative | 1 |
Education Level
| High Schools | 1 |
| Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| National Longitudinal Study… | 1 |
What Works Clearinghouse Rating
Han Du; Brian Keller; Egamaria Alacam; Craig Enders – Grantee Submission, 2023
In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…
Descriptors: Bayesian Statistics, Models, Comparative Analysis, Probability
Hardy, Jessica K.; McLeod, Ragan H.; Sweigart, Chris A.; Landrum, Timothy – Infants and Young Children, 2022
The purpose of this study was to compare and contrast frameworks for evaluating methodological rigor in single case research. Specifically, research on high-probability requests to increase compliance in young children was evaluated. Ten studies were identified and were coded using 4 frameworks. These frameworks were the Council for Exceptional…
Descriptors: Case Studies, Research Methodology, Probability, Compliance (Psychology)
Duxbury, Scott W. – Sociological Methods & Research, 2023
This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…
Descriptors: Graphs, Scaling, Research Problems, Models

Peer reviewed
Direct link
