We read with great interest Dr. Greenland’s invited com-mentary (1) about variable selection to control for confound-ing in observational studies. We agree with Dr. Greenland that the identification of confounders should be based primar-ily on background knowledge and not on significance testing. However, our proposed method (2) is not meant primarily as a variable selection procedure. Currently, relative risk esti-mates are commonly presented from nested models with in-creasing complexity of covariate use (3). This is not caused predominantly by the uncertainty of selecting the proper model, but rather by the interest to quantify the relative effect of adjustment for specific covariates on risk estimates. For example, relative risks from a...
This note demonstrates that in applied regression analysis, the variance of a coeffi cient of intere...
reviewers offered important insights to the development of this work. I am indebted to Feng Sun for ...
We appreciate the opportunity to reflect on the thoughtful commentary by Schisterman et al. (1). Dir...
After screening out inappropriate or doubtful covariates on the basis of background knowledge, one m...
We establish a link between the approaches proposed by Oster (2019) and Pei, Pischke, and Schwandt (...
In our paper (1), we considered the extent and patterns of bias in estimates of exposure-outcome ass...
Confounder selection is perhaps the most important step in the design of observational studies. A nu...
Standard variable selection procedures, primarily developed for the construction of outcome predicti...
In confounding, the effect of the exposure of interest is mixed with the effect of another variable....
Inferring the causal effect of a treatment on an outcome in an observational study requires adjustin...
Concern over the impact of flawed measurement continues to nag epidemiology. Early studies indicated...
Confounders can be identified by one of two main strategies: empirical or theoretical. Although conf...
As a natural experiment, random inheritance of alleles promises to allow unveiling causal effects of...
The assumption of strongly ignorable treatment assignment is required for eliminating selection bias...
Observational studies can play a useful role in assessing the comparative effectiveness of competing...
This note demonstrates that in applied regression analysis, the variance of a coeffi cient of intere...
reviewers offered important insights to the development of this work. I am indebted to Feng Sun for ...
We appreciate the opportunity to reflect on the thoughtful commentary by Schisterman et al. (1). Dir...
After screening out inappropriate or doubtful covariates on the basis of background knowledge, one m...
We establish a link between the approaches proposed by Oster (2019) and Pei, Pischke, and Schwandt (...
In our paper (1), we considered the extent and patterns of bias in estimates of exposure-outcome ass...
Confounder selection is perhaps the most important step in the design of observational studies. A nu...
Standard variable selection procedures, primarily developed for the construction of outcome predicti...
In confounding, the effect of the exposure of interest is mixed with the effect of another variable....
Inferring the causal effect of a treatment on an outcome in an observational study requires adjustin...
Concern over the impact of flawed measurement continues to nag epidemiology. Early studies indicated...
Confounders can be identified by one of two main strategies: empirical or theoretical. Although conf...
As a natural experiment, random inheritance of alleles promises to allow unveiling causal effects of...
The assumption of strongly ignorable treatment assignment is required for eliminating selection bias...
Observational studies can play a useful role in assessing the comparative effectiveness of competing...
This note demonstrates that in applied regression analysis, the variance of a coeffi cient of intere...
reviewers offered important insights to the development of this work. I am indebted to Feng Sun for ...
We appreciate the opportunity to reflect on the thoughtful commentary by Schisterman et al. (1). Dir...