Pooling data is crucial in epidemiology for several reasons:
Increased Statistical Power: Combining data from multiple sources increases the sample size, leading to more robust and credible results. Enhanced Generalizability: By integrating diverse data, the findings are more likely to be generalizable across different populations and settings. Reduction of Bias: Pooling data can help mitigate biases that may be present in individual studies, leading to more accurate conclusions.
