Several strategies can be employed to reduce biases in observational studies:
- Matching: This involves pairing cases and controls based on certain characteristics (e.g., age, smoking status) to reduce confounding variables. - Statistical Adjustments: Techniques such as multivariate analysis can adjust for potential confounders. - Propensity Score Matching: This method involves creating a statistical score based on observed covariates to balance the characteristics between treated and untreated groups.
