Understanding data heterogeneity is critical for several reasons:
1. Bias and Confounding: Heterogeneous data can introduce bias and confounding factors, which can mislead the interpretation of study results. 2. Generalizability: Knowing the extent of heterogeneity helps in assessing the generalizability of the study findings to other populations. 3. Precision: Accounting for heterogeneity can improve the precision of estimates and lead to more reliable conclusions.
