Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 2 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Causal Models | 3 |
| Context Effect | 3 |
| Statistical Inference | 3 |
| Educational Research | 2 |
| Regression (Statistics) | 2 |
| Research Design | 2 |
| Accuracy | 1 |
| Aptitude Treatment Interaction | 1 |
| Data Collection | 1 |
| Educational Policy | 1 |
| Graphs | 1 |
| More ▼ | |
Author
| Han, Tianqi | 1 |
| Kenneth A. Frank | 1 |
| Peter M. Steiner | 1 |
| Qinyun Lin | 1 |
| Sheehan, Janet K. | 1 |
| Spiro J. Maroulis | 1 |
| Yi Feng | 1 |
Publication Type
| Information Analyses | 1 |
| Journal Articles | 1 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Yi Feng; Peter M. Steiner – Society for Research on Educational Effectiveness, 2022
Research Context: In educational research, "context effects" are often of inferential interest to researchers as well as of evaluative interest to policymakers. While student education outcomes likely depend on individual-level influences like individual academic achievement, school contexts may also make a difference. Such questions are…
Descriptors: Hierarchical Linear Modeling, Accuracy, Graphs, Educational Research
Peer reviewedKenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy
Peer reviewedSheehan, Janet K.; Han, Tianqi – Mid-Western Educational Researcher, 1996
Contrasts aptitude by treatment interaction (ATI) and hierarchical linear modeling (HLM) methods for making cross-level inferences between individual-level and group-level factors in school effectiveness research. Recommends HLM when intraclass correlations are high. ATI is suitable when intraclass correlations are low, but partitioning the…
Descriptors: Aptitude Treatment Interaction, Causal Models, Context Effect, Educational Research

Direct link
