Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource, 1 online resource.
- Language
-
Englisch
- Bibliographic citation
-
Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables ; volume:23 ; number:1 ; day:22 ; month:5 ; year:2023 ; pages:1-24 ; date:12.2023
BMC medical research methodology ; 23, Heft 1 (22.5.2023), 1-24, 12.2023
- Creator
-
Zawadzki, Roy S.
Grill, Joshua D.
Gillen, Daniel L.
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s12874-023-01936-2
- URN
-
urn:nbn:de:101:1-2023091011492166411014
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:54 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zawadzki, Roy S.
- Grill, Joshua D.
- Gillen, Daniel L.
- SpringerLink (Online service)
Other Objects (12)
Causal inference with imperfect instrumental variables
Modified Causal Forests for Estimating Heterogeneous Causal Effects
Analytic comparison of pearl and rubin's causal frameworks
Causal random forests model using instrumental variable quantile regression
Confounding-adjustment methods for the causal difference in medians
Estimating and testing non-linear models using instrumental variables
Viewpoint: Estimating the Causal Effects of Policies and Programs
Athletic Injury Research: Frameworks, Models and the Need for Causal Knowledge
Non-parametric adjustment for covariates when estimating a treatment effect
Estimating the impact of quality adjustment on consumer price inflation
Estimating the impact of quality adjustment on consumer price inflation
Estimating the impact of quality adjustment on consumer price inflation
Causal inference with imperfect instrumental variables
Modified Causal Forests for Estimating Heterogeneous Causal Effects
Analytic comparison of pearl and rubin's causal frameworks
Causal random forests model using instrumental variable quantile regression
Confounding-adjustment methods for the causal difference in medians
Estimating and testing non-linear models using instrumental variables
Viewpoint: Estimating the Causal Effects of Policies and Programs
Athletic Injury Research: Frameworks, Models and the Need for Causal Knowledge
Non-parametric adjustment for covariates when estimating a treatment effect
Estimating the impact of quality adjustment on consumer price inflation
Estimating the impact of quality adjustment on consumer price inflation
Estimating the impact of quality adjustment on consumer price inflation
Causal inference with imperfect instrumental variables
Modified Causal Forests for Estimating Heterogeneous Causal Effects
Analytic comparison of pearl and rubin's causal frameworks
Causal random forests model using instrumental variable quantile regression
Confounding-adjustment methods for the causal difference in medians
Estimating and testing non-linear models using instrumental variables
Viewpoint: Estimating the Causal Effects of Policies and Programs
Athletic Injury Research: Frameworks, Models and the Need for Causal Knowledge
Non-parametric adjustment for covariates when estimating a treatment effect
Estimating the impact of quality adjustment on consumer price inflation
Estimating the impact of quality adjustment on consumer price inflation