Publication Date
| In 2025 | 1 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Causal Models | 1 |
| Comparative Testing | 1 |
| Elementary School Students | 1 |
| Elementary School Teachers | 1 |
| Generalization | 1 |
| Quasiexperimental Design | 1 |
| Randomized Controlled Trials | 1 |
| Research Methodology | 1 |
| Test Bias | 1 |
| Test Construction | 1 |
| Test Selection | 1 |
| More ▼ | |
Author
| Andrew P. Jaciw | 1 |
Publication Type
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
Education Level
| Elementary Education | 1 |
Audience
Location
| Tennessee | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkAndrew P. Jaciw – American Journal of Evaluation, 2025
By design, randomized experiments (XPs) rule out bias from confounded selection of participants into conditions. Quasi-experiments (QEs) are often considered second-best because they do not share this benefit. However, when results from XPs are used to generalize causal impacts, the benefit from unconfounded selection into conditions may be offset…
Descriptors: Elementary School Students, Elementary School Teachers, Generalization, Test Bias
