Several factors contribute to ambiguity in epidemiological studies:
Measurement error: Inaccuracies in data collection can lead to misclassification of exposures or outcomes, thus introducing bias. Confounding variables: These are extraneous variables that correlate with both the independent and dependent variables, potentially leading to erroneous conclusions. Selection bias: This occurs when the study sample is not representative of the target population, affecting the generalizability of the findings. Information bias: Systematic errors in the collection, recall, or interpretation of data can distort the study results.
