konfounderende

Konfounderende is an adjective used in statistics, epidemiology, and research design to describe factors that distort the observed relationship between an exposure and an outcome. In this context, a konfounderende variabel (confounding variable) is a variable that is associated with both the exposure and the outcome and is not on the causal path from exposure to outcome. Such a variable can create a spurious or biased estimate of the effect being studied.

A common consequence of konfoundering is that an observed association may reflect the influence of the confounder rather than a direct effect of the exposure. For example, in observational studies of a beverage and a health outcome, age or socioeconomic status can be konfunderende if they relate to both consumption and disease risk, leading to misleading conclusions about causality.

Addressing konfoundering is a central concern in study design and analysis. Randomization in experimental designs helps balance confounders across groups. In observational studies, researchers may use restriction (limiting the study to a specific subset), matching (pairing subjects with similar confounders), stratification (analyzing within levels of the confounder), or multivariable adjustment (regression models that include confounders). Propensity score methods balance groups on observed confounders, while instrumental variable analysis can address unmeasured confounding under specific assumptions. Sensitivity analyses assess how robust findings are to potential konfounding.

Etymology-wise, konfounderende derives from the verb to confound, meaning to confuse or mix together. In causal inference, distinguishing konfoundering from mediation and collider bias is essential for valid conclusions.