This analysis reveals the effects of confounding on causal relationships in studies, highlighting its significance.
onfounding should always be addressed in studies concerned with causality. When present, it results in a biased estimate of the effect of exposure on disease. The bias can be negative-resulting in underestimation of the exposure effect-or positive, and can even reverse the apparent direction of effect. It is a concern no matter what the design of the study or what statistic is used to measure the effect of exposure.
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Roseanne McNamee (2003) studied this question.
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