Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Bayesian Statistics | 2 |
| Children | 2 |
| Longitudinal Studies | 2 |
| Markov Processes | 2 |
| Models | 2 |
| Monte Carlo Methods | 2 |
| Surveys | 2 |
| Attendance | 1 |
| Computation | 1 |
| Grade 1 | 1 |
| Kindergarten | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
| Reports - Research | 1 |
Education Level
| Early Childhood Education | 1 |
| Elementary Education | 1 |
| Grade 1 | 1 |
| Kindergarten | 1 |
| Primary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| Early Childhood Longitudinal… | 2 |
What Works Clearinghouse Rating
Zhang, Zhiyong – Grantee Submission, 2016
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is…
Descriptors: Bayesian Statistics, Models, Statistical Distributions, Computation
Kaplan, David; Chen, Jianshen – Society for Research on Educational Effectiveness, 2013
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Descriptors: Bayesian Statistics, Models, Probability, Monte Carlo Methods

Peer reviewed
Direct link
