Researchers can employ several strategies to address non-independence:
1. Stratification: This involves analyzing data within strata (subgroups) where the variables are more likely to be independent. 2. Multivariable Analysis: Techniques like multivariable regression can adjust for multiple confounders simultaneously, helping to isolate the independent effect of each variable. 3. Randomization: In experimental studies, randomization helps ensure that the exposure is independent of other variables, reducing the risk of confounding.
