Simultaneity bias occurs when two or more variables affect each other simultaneously, making it difficult to determine the direction of causation. This issue arises in observational studies where the independent and dependent variables influence each other, leading to misleading results. Understanding simultaneity bias is crucial because it challenges the validity of causal claims drawn from data that does not adequately account for these interdependencies.
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