Add to ORKGConfounder selection is perhaps the most important step in the design of observational studies. A number of criteria, often with different objectives and approaches, have been proposed, and their validity and practical value have been debated in the literature. Here, we provide a unified review of these criteria and the assumptions behind them. We list several objectives that confounder selection methods aim to achieve and discuss the amount of structural knowledge required by different approaches. Finally, we discuss limitations of the existing approaches and implications for practitioners.Comment: 15 page
Background : A review of epidemiological papers conducted in 2009 concluded that several studies emp...
The ability to compare similar groups is central to causal inference. If two groups are the same exc...
Conditioning on some set of confounders that causally affect both treatmentand outcome variables can...
We propose a new criterion for confounder selection when the underlying causal structure is unknown ...
Inferring the causal effect of a treatment on an outcome in an observational study requires adjustin...
The causal inference literature has provided a clear formal definition of confounding expressed in t...
The aim of causal effect estimation is to find the true impact of a treatment or exposure. Observati...
The assumption of strongly ignorable treatment assignment is required for eliminating selection bias...
Description of prior research and/or its intellectual context and/or its policy context. In observat...
We read with great interest Dr. Greenland’s invited com-mentary (1) about variable selection to cont...
After screening out inappropriate or doubtful covariates on the basis of background knowledge, one m...
The paper addresses a formal definition of a confounder based on the qualitative definition that is ...
In confounding, the effect of the exposure of interest is mixed with the effect of another variable....
Confounders can be identified by one of two main strategies: empirical or theoretical. Although conf...
Nonexperimental studies are increasingly used to investigate the safety and effectiveness of medical...
Background : A review of epidemiological papers conducted in 2009 concluded that several studies emp...
The ability to compare similar groups is central to causal inference. If two groups are the same exc...
Conditioning on some set of confounders that causally affect both treatmentand outcome variables can...
We propose a new criterion for confounder selection when the underlying causal structure is unknown ...
Inferring the causal effect of a treatment on an outcome in an observational study requires adjustin...
The causal inference literature has provided a clear formal definition of confounding expressed in t...
The aim of causal effect estimation is to find the true impact of a treatment or exposure. Observati...
The assumption of strongly ignorable treatment assignment is required for eliminating selection bias...
Description of prior research and/or its intellectual context and/or its policy context. In observat...
We read with great interest Dr. Greenland’s invited com-mentary (1) about variable selection to cont...
After screening out inappropriate or doubtful covariates on the basis of background knowledge, one m...
The paper addresses a formal definition of a confounder based on the qualitative definition that is ...
In confounding, the effect of the exposure of interest is mixed with the effect of another variable....
Confounders can be identified by one of two main strategies: empirical or theoretical. Although conf...
Nonexperimental studies are increasingly used to investigate the safety and effectiveness of medical...
Background : A review of epidemiological papers conducted in 2009 concluded that several studies emp...
The ability to compare similar groups is central to causal inference. If two groups are the same exc...
Conditioning on some set of confounders that causally affect both treatmentand outcome variables can...