Bias and confounding are significant threats to the quality of epidemiological studies. Bias can stem from selection, information, or measurement errors, leading to inaccurate results. Confounding occurs when an extraneous variable influences both the dependent and independent variables, distorting the true relationship. Researchers must use strategies like randomization, matching, stratification, and statistical adjustments to mitigate these issues.
