Cameron Guage
Biographic Data
| ID | 6909922 |
|---|---|
| NAME | Cameron Guage |
| GIVEN NAMES | Cameron |
| FAMILY NAME | Guage |
| SIGNATURE | GUAGE C |
| AFFILIATIONS | Dartmouth College |
| ORCID | 0000-0003-0539-4099 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Monotone Ecological Inference
We study the identification of individual-level associations when only aggregate data are available. We characterize the biases of, and relationships among, canonical ecological inference (EI) estimators. We use these results to develop a partial identification approach: monotone EI. The approach exploits information about one or both of the following conditional associations: (1) outcome differences between groups within the same neighborhood an…
Americans do not select their doctors based on race
To what extent do Americans racially discriminate against doctors? While a large literature shows that racial biases pervade the American healthcare system, there has been no systematic examination of these biases in terms of who patients select for medical treatment. We examine this question in the context of the ongoing global COVID-19 pandemic, where a wealth of qualitative evidence suggests that discrimination against some historically margin…
No prominent works on this page.
Americans do not select their doctors based on race
To what extent do Americans racially discriminate against doctors? While a large literature shows that racial biases pervade the American healthcare system, there has been no systematic examination of these biases in terms of who patients select for medical treatment. We examine this question in the context of the ongoing global COVID-19 pandemic, where a wealth of qualitative evidence suggests that discrimination against some historically margin…
Monotone Ecological Inference
We study the identification of individual-level associations when only aggregate data are available. We characterize the biases of, and relationships among, canonical ecological inference (EI) estimators. We use these results to develop a partial identification approach: monotone EI. The approach exploits information about one or both of the following conditional associations: (1) outcome differences between groups within the same neighborhood an…
Advanced Causal Inference Techniques (1 work) · Context (archaeology (1 work) · Coronavirus disease 2019 (COVID-19 (1 work) · COVID-19 epidemiological studies (1 work) · Ethnic group (1 work) · Gender Studies (1 work) · Gender Studies (1 work) · Geography (1 work) · Group (periodic table) (1 work) · Health care (1 work)