Contents
What does confounding mean in research?
What is confounding? Confounding is often referred to as a “mixing of effects”1,2 wherein the effects of the exposure under study on a given outcome are mixed in with the effects of an additional factor (or set of factors) resulting in a distortion of the true relationship.
What is confounded relationship in research?
Confounding means the distortion of the association between the independent and dependent variables because a third variable is independently associated with both. A causal relationship between two variables is often described as the way in which the independent variable affects the dependent variable.
What is confounding bias in research?
Confounding bias: A systematic distortion in the measure of association between exposure and the health outcome caused by mixing the effect of the exposure of primary interest with extraneous risk factors.
What is an example of confounding variables?
A confounding variable is an “extra” variable that you didn’t account for. They can ruin an experiment and give you useless results. For example, if you are researching whether lack of exercise leads to weight gain, then lack of exercise is your independent variable and weight gain is your dependent variable.
What’s an example of confounding?
Why is confounding a special case in epidemiology?
I prefer the term confounding, without the word bias, because while it also leads to a systematic error in the data, confounding is a special case. Imagine that you are doing a cross-sectional study in elementary school-aged kids of foot size and reading ability:
Is there a causal link between confounding and an outcome?
In this case, there must be a causal link between the confounder and the outcome. It does not have to be a proven causal link, just an “it is reasonably possible that this exposure causes (or prevents) that outcome” link. In our foot size/reading ability example, grade level (the confounder) certainly causes faster reading speed (the outcome).
Which is the best definition of a confounding variable?
Confounding: Definition A confounder is thus a third variable—not the exposure, and not the outcome —that biases the measure of association we calculate for the particular exposure/outcome pair. Importantly, from a research perspective, we never want to report a measure of association that is confounded.
What does Association mean in relation to confounding variables?
Basically, association means that the confounding variable is more common in the exposed group than the unexposed group (or vice versa), thus producing a statistical association. The confounder does not need to cause or prevent the exposure, it just needs to be disproportionately distributed between the exposed and unexposed groups.