Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables

Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables

Abstract To estimate causal effects, analysts performing observational studies in health settings utilize several strategies to mitigate bias due to confounding by indication. There are two broad classes of approaches for these purposes: use of confounders and instrumental variables (IVs). Because s...

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Bibliographic Details
Main Authors: Roy S. Zawadzki, Joshua D. Grill, Daniel L. Gillen, and for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: BMC 2023-05-01
Series:BMC Medical Research Methodology
Subjects:
Causal inference
Observational studies
Instrumental variables
Adjustment
Propensity scores
Online Access:https://doi.org/10.1186/s12874-023-01936-2

Internet

https://doi.org/10.1186/s12874-023-01936-2

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