Bias and confounding are major challenges in epidemiological studies. Selection bias may occur if the study population is not representative of the general population, while information bias can arise from inaccurate data collection. Confounding occurs when an extraneous factor is associated with both the risk factor and the outcome. Techniques such as statistical adjustments, stratification, and multivariable modeling are used to minimize these issues and ensure valid results.
