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**What is confounding in a study? 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 confounding in research?** A Confounder is an extraneous variable whose presence affects the variables being studied so that the results do not reflect the actual relationship between the variables under study.

**What is an example of a confounding variable?** A confounding variable is an outside influence that changes the effect of a dependent and independent variable. For example, if you are researching whether a lack of exercise has an effect on weight gain, the lack of exercise is the independent variable and weight gain is the dependent variable.

**How do you find confounders in a study?** Identifying Confounding

In other words, compute the measure of association both before and after adjusting for a potential confounding factor. If the difference between the two measures of association is 10% or more, then confounding was present. If it is less than 10%, then there was little, if any, confounding.

to perplex or amaze, especially by a sudden disturbance or surprise; bewilder; confuse: The complicated directions confounded him. to throw into confusion or disorder: The revolution confounded the people.

In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) is a variable that influences both the dependent variable and independent variable, causing a spurious association.

Ignoring confounding when assessing the associ- ation between an exposure and an outcome variable can lead to an over- estimate or underestimate of the true association between exposure and outcome and can even change the direction of the observed effect.

The magnitude of confounding is the percent difference between the crude and adjusted measures of association, calculated as follows (for either a risk ratio or an odds ratio): If the % difference is 10% or greater, we conclude that there was confounding.

One of the method for controlling the confounding variables is to run a multiple logistic regression. You can apply binary logistics regression if the outcome (Dependent ) variable is binary (Yes/No). In logistics regression model, under the covariates include the independent and confounding variables.

Confounding: 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.

Potential confounders were defined as variables shown in the literature to be causally associated with the outcome (HIV RNA suppression) and associated with exposure in the source population (hunger) but not intermediate variables in the causal pathway between exposure and outcome [4,31,32].

adjective. bewildered; confused; perplexed.

Confounding in a Sentence

1. My dog is usually friendly and cheerful, so his reclusive and hostile behavior today is absolutely confounding. 2. Why anyone would choose to explore a dark cave is confounding to me, but some people enjoy the mystery and the danger.

Confounding is one type of systematic error that can occur in epidemiologic studies. Confounding is the distortion of the association between an exposure and health outcome by an extraneous, third variable called a confounder.

Complete confounding means that you confound the same effects in every replication. The efficiency of the estimate is the fraction of replicates where the effect is not confounded. E.g., three replications and only confounded in one is 2/3 efficiency.

ANCOVA can control for other factors that might influence the outcome. For example: family life, job status, or drug use.

A confounding variable is a third variable that influences both the independent and dependent variables. Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

In randomization the random assignment of study subjects to exposure categories to breaking any links between exposure and confounders. This reduces potential for confounding by generating groups that are fairly comparable with respect to known and unknown confounding variables.

A situation in which the effect or association between an exposure and outcome is distorted by the presence of another variable. Positive confounding (when the observed association is biased away from the null) and negative confounding (when the observed association is biased toward the null) both occur.

The most fulminant form of confounding is known as qualitative confounding, aka a reversal of effect or Simpson’s Paradox. For example, the crude estimate is 4.0 meaning the exposure in question carries a 4 fold risk for disease, but the adjusted estimate is actually protective.

A change in the estimated measure of association of 10% or more would be evidence that confounding was present, but if the measure of association changes by <10%, there is likely to be little, if any, confounding by that variable.

Confounders are variables that are related to both the intervention and the outcome, but are not on the causal pathway. Covariates are variables that explain a part of the variability in the outcome.

Confounding variables are those that affect other variables in a way that produces spurious or distorted associations between two variables. They confound the “true” relationship between two variables.

Bias creates an association that is not true, but confounding describes an association that is true, but potentially misleading.

Methods used for controlling for confounding at the design stage Restriction Restriction is a method that limits participation in the study to individuals who are similar in relation to the confounder. For example, a study restricted to non-smokers only will eliminate any confounding effect of smoking.