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
| Comparative Analysis | 2 |
| Hierarchical Linear Modeling | 2 |
| Multiple Regression Analysis | 2 |
| Value Added Models | 2 |
| Academic Achievement | 1 |
| Access to Education | 1 |
| Achievement Gap | 1 |
| At Risk Students | 1 |
| Blacks | 1 |
| Children | 1 |
| Correlation | 1 |
| More ▼ | |
Source
| Pearson | 1 |
| Review of Education | 1 |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
Education Level
| Elementary Education | 2 |
Audience
Location
| Texas | 1 |
| United Kingdom | 1 |
| United Kingdom (London) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Direct linkWei, Hua; Hembry, Tracey; Murphy, Daniel L.; McBride, Yuanyuan – Pearson, 2012
This study compared five value-added models and illustrated the impact of model choice on the estimates of teacher effectiveness. The five models covered a broad range of technical procedures, some very simplistic and others very sophisticated. The five value-added models were applied to a common data set to generate teacher-effectiveness measures…
Descriptors: Value Added Models, Teacher Evaluation, Teacher Effectiveness, Comparative Analysis
Peer reviewedStrand, Steve – Review of Education, 2016
Relatively little research has explored whether schools differ in their effectiveness for different group of pupils (e.g. by ethnicity, poverty or gender), for different curriculum subjects (e.g. English, mathematics or science) or over time (different cohorts). This paper uses multilevel modelling to analyse the national test results at age 7 and…
Descriptors: School Effectiveness, Hierarchical Linear Modeling, Children, Elementary School Students
