what is a confounding factor in research?
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Confounding variables are those that may compete with the exposure of interest (eg, treatment) in explaining the outcome of a study. The amount of association “above and beyond” that which can be explained by confounding factors provides a more appropriate estimate of the true association which is due to the exposure.
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In epidemiology, confounding variables to signify a covariate that is related to both predictors & treatment/exposure. There are also who focus on the effect of a confounder: "A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship".
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['Control over variables. This kind of research looks into controlling independent variables so that extraneous and unwanted variables are removed.', 'Determination of cause and effect relationship is easy. ... ', 'Provides better results.']
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Confounding is an important concept in epidemiology, because, if present, it can cause an over- or under- estimate of the observed association between exposure and health outcome. ... Confounding is a bias because it can result in a distortion in the measure of association between an exposure and health outcome.
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Effect modification is distinct from confounding; it occurs when the magnitude of the effect of the primary exposure on an outcome (i.e., the association) differs depending on the level of a third variable.
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Research is conducted in a methodical manner without bias using systematic method and procedures. 7. Replicability. The research design and procedures are replicated or repeated to enable the researcher to arrive at valid and conclusive results.
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Confounders. A confounder (or 'confounding factor') is something, other than the thing being studied, that could be causing the results seen in a study.
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In research, an experimenter bias, also known as research bias, occurs when a researcher unconsciously affects results, data, or a participant in an experiment due to subjective influence. It is difficult for humans to be entirely objective which is not being influenced by personal emotions, desires, or biases.
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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. A confounding variable would be any other influence that has an effect on weight gain.
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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.
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In a controlled study, researchers are able to determine which of their subjects receive the factor that is being tested for having a causal influence upon another factor. ... In uncontrolled or observational studies, researchers have no such control over whether their subjects receive the treatment being investigated.
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Bias is any error resulting from methods used by the investigator to recruit individuals for the study, from factors affecting the study participation (selection bias) or from systematic distortions when collecting information about exposures and diseases (information bias).
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Bias creates an association that is not true, but confounding describes an association that is true, but potentially misleading.
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Time varying confounding occurs when confounders have values that change over time. It often occurs with time varying exposures. Many exposures of epidemiological interest are time varying—for example, treatment dose, body mass index, smoking status, blood pressure, depression, air pollution, socioeconomic status.
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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.
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Confound. Confounding is when a researcher does not control some extraneous variables that may influence the results...the only variable that should influence the results is the variable being studied. ... This is a very serious problem since the researcher can't really claim that he/she established cause and effect.
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A particularly important type of confounding in clinical research is “confounding by indication,” which occurs when the clinical indication for selecting a particular treatment (eg, severity of the illness) also affects the outcome.