PURPOSE: Uncontrolled confounders are an important source of bias in epidemiologic
studies. The authors review and derive a set of parallel simple formulas for bias factors in the …

Measurement error in explanatory variables and unmeasured confounders can cause
considerable problems in epidemiologic studies. It is well recognized that under certain …

Abstract Purpose of Review This review expands on sensitivity analyses for unmeasured
confounding techniques, demonstrating state-of-the-art methods as well as specifying which …

Quantitative bias analyses allow researchers to adjust for uncontrolled confounding, given
specification of certain bias parameters. When researchers are concerned about unknown …

Purpose Observational studies are prone to (unmeasured) confounding. Sensitivity analysis
of unmeasured confounding typically focuses on a single unmeasured confounder. The …

After screening out inappropriate or doubtful covariates on the basis of background
knowledge, one may still be left with many potential confounders. It is then tempting to use …

Background: Epidemiologic studies that aim to estimate a causal effect of an exposure on a
particular event of interest may be complicated by the existence of competing events that …

In the absence of prior knowledge about population relations, investigators frequently
employ a strategy that uses the data to help them decide whether to adjust for a variable …

It is common to present multiple adjusted effect estimates from a single model in a single
table. For example, a table might show odds ratios for one or more exposures and also for …

This paper addresses potential effects of non-differential misclassification of polytomous
confounders on adjusted exposure-disease associations. Although the degree of …