Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 1 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 1 |
Descriptor
| Algorithms | 1 |
| Artificial Intelligence | 1 |
| Bayesian Statistics | 1 |
| Causal Models | 1 |
| Comparative Analysis | 1 |
| Data Analysis | 1 |
| Generalizability Theory | 1 |
| Regression (Statistics) | 1 |
| Statistical Inference | 1 |
Source
| Grantee Submission | 1 |
Author
| George Perrett | 1 |
| Jennifer Hill | 1 |
| Vincent Dorie | 1 |
Publication Type
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full text
Direct linkJennifer Hill; George Perrett; Vincent Dorie – Grantee Submission, 2023
Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…
Descriptors: Causal Models, Statistical Inference, Artificial Intelligence, Data Analysis
