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Türkisch - Englisch
confounding
Said of two or more possible causes of an observed statistically significant effect when statistical analysis cannot determine which is the cause
Finding an association for the wrong reason
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
When the differences between the treatment and control groups other than the treatment produce differences in response that are not distinguishable from the effect of the treatment, those differences between the groups are said to be confounded with the effect of the treatment (if any) For example, prominent statisticians questioned whether differences between individuals that led some to smoke and others not to (rather than the act of smoking itself) were responsible for the observed difference in the frequencies with which smokers and non-smokers contract various illnesses If that were the case, those factors would be confounded with the effect of smoking Confounding is quite likely to affect observational studies and experiments that are not randomized Confounding tends to be decreased by randomization See also Simpson's Paradox
present participle of confound
Occurs when the independent variable of interest systematically covaries with a second, unintended independent variable
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 measured effect attributed to a variable that is actually due to an unmeasured co-variable
A relationship between 2 (or more) variables which prevents their effects from being evaluated separately Confounding can affect either Independent or Dependent variables and causes problems in interpreting which variable caused the experimental effect to occur
The distortion of an apparent effect of an exposure on risk, brought about by the association with other factors that can influence the outcome For example, a study might suggest that alcohol intake is associated with a higher risk of heart disease, but this apparent relationship is seen because those who drink alcohol are also more inclined to smoke When their smoking is taken into consideration, the relationship between alcohol intake and heart disease disappears Congenital: referring to conditions that are present at birth
that confounds or contradicts or confuses
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