An Interval for Unmeasured Residual Confounding
نویسندگان
چکیده
منابع مشابه
Using an instrumental variable to test for unmeasured confounding.
An important concern in an observational study is whether or not there is unmeasured confounding, that is, unmeasured ways in which the treatment and control groups differ before treatment, which affect the outcome. We develop a test of whether there is unmeasured confounding when an instrumental variable (IV) is available. An IV is a variable that is independent of the unmeasured confounding a...
متن کاملSensitivity analysis for interactions under unmeasured confounding.
We develop a sensitivity analysis technique to assess the sensitivity of interaction analyses to unmeasured confounding. We give bias formulas for sensitivity analysis for interaction under unmeasured confounding on both additive and multiplicative scales. We provide simplified formulas in the case in which either one of the two factors does not interact with the unmeasured confounder in its ef...
متن کاملThe impact of residual and unmeasured confounding in epidemiologic studies: a simulation study.
Measurement error in explanatory variables and unmeasured confounders can cause considerable problems in epidemiologic studies. It is well recognized that under certain conditions, nondifferential measurement error in the exposure variable produces bias towards the null. Measurement error in confounders will lead to residual confounding, but this is not a straightforward issue, and it is not cl...
متن کاملSharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding
It is often of interest to decompose the total effect of an exposure into a component that acts on the outcome through some mediator and a component that acts independently through other pathways. Said another way, we are interested in the direct and indirect effects of the exposure on the outcome. Even if the exposure is randomly assigned, it is often infeasible to randomize the mediator, leav...
متن کاملPropensity Score Adjustment for Unmeasured Confounding in Observational Studies
Adjusting for several unmeasured confounders is a challenging problem in the analysis of observational data. Information about unmeasured confounders is sometimes available from external validation data, such as surveys or secondary samples drawn from the same source population. In principal, the validation permits us to recover information about the missing data, but the difficulty is in elici...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Environmental Epidemiology
سال: 2019
ISSN: 2474-7882
DOI: 10.1097/01.ee9.0000608344.72030.34