title: [Bias in observational research: 'confounding'].
abstract: Confounding is an important and common issue in observational (non-randomized) research on the effects of pharmaceuticals or exposure to etiologic factors (determinants). Confounding is present when a third factor, related to both the determinant and the outcome, distorts the causal relation between these two. There are different methods to control for confounding. The most commonly used are restriction, stratification, multivariable regression models, and propensity score methods. With these methods it is only possible to control for variables for which data is known: measured confounders. Research in the area of confounding is currently directed at the incorporation of external knowledge on unmeasured confounders, the evaluation of instrumental variables, and the impact of time-dependent confounding.
authors.affiliation: Julius Centrum voor Gezondheidswetenschappen en Eerstelijns Gezondheidszorg, Universitair Medisch Centrum Utrecht, Utrecht, The Netherlands. r.h.h.groenwold@umcutrecht.nl
authors.forename: Rolf H H
authors.initials: RH
authors.lastname: Groenwold
mesh_terms: D015982:Bias; D015986:Confounding Factors, Epidemiologic; D006801:Humans; D015233:Models, Statistical; D015588:Observer Variation; D012106:Research / Q000592:standards*