Allowing two or more variables to vary together so that it is impossible to separate their unique effects.

Confounding is considered a "mixing of effects". When a factor X causes a disease Y, that relationship could be confounded by a factor C that is associated with both factor X and disease Y. C would be an alternative explanation for the relationship observed between X and Y.

A mixing of effects. The exposure - disease association is distorted by a third factor, which is associated with both of the other two variables.

when experimental groups differ on two or more factors simultaneously

This occurs when the apparent relationship between a predictor and outcome is influenced by other factors, some of which might be unmeasured or unrealized. Scientists can use study designs and analytic strategies to control for confounding in their research.

An inability to distinguish the separate impacts of two or more individual variables on a single outcome.

A confounding design is one where some treatment effects (main or interactions) are estimated by the same linear combination of the experimental observations as some blocking effects. In this case, the treatment effect and the blocking effect are said to be confounded. Confounding is also used as a general term to indicate that the value of a main effect estimate comes from both the main effect itself and also contamination or bias from higher order interactions. Note: Confounding designs naturally arise when full factorial designs have to be run in blocks and the block size is smaller than the number of different treatment combinations. They also occur whenever a fractional factorial design is chosen instead of a full factorial design.

an extraneous variable that has not been recognized or controlled

epidemiologic term describing characteristics closely linked to the exposure under study, possibly leading to incomplete or incorrect conclusions. For example, maternal obesity is linked to neural tube defects. Does obesity cause neural tube defects directly? Or is a linked factorâ€”such as nutrition, altered metabolism or underlying genetic defectâ€”responsible

Extraneous variables resulting in outcome effects that obscure or exaggerate the "true" effect of an intervention.

A measured effect attributed to a variable that is actually due to an unmeasured co-variable.

The undesired mixing of effects of extraneous risk factors with the main effect of the targeted risk factor(s). The influence of cofactors (e.g., smoking) biases (distorts) the observed main effect of interest (e.g., dusts and lung cancer). Confounding is usually controlled for by multivariate analysis and other statistical adjustment techniques.

Confounding variables are factors - such as overcrowding and malnutrition, in the case of childhood... view

One or more effects that cannot unambiguously be attributed to a single factor or interaction.

The distortion of a measure of the effect of an exposure (eg to therapy involving the proposed drug) on the risk of an outcome under investigation brought about by the association of the exposure with other factor(s) that can influence the outcome.

A situation in which the estimated intervention effect is biased because of some difference between the comparison groups apart from the planned interventions, such as baseline characteristics, prognostic factors, or concomitant interventions. For a factor to be a confounder, it must differ between the comparison groups and predict the outcome of interest. See also Adjusted analysis.