Improved Precision: By including more participants from specific subgroups, researchers can obtain more reliable estimates and confidence intervals. Enhanced Statistical Power: Oversampling increases the statistical power to detect differences or associations within subgroups. Bias Reduction: It helps in reducing potential biases that result from underrepresented groups in the sample. Better Subgroup Analysis: Allows for more detailed and accurate analysis of subgroup-specific outcomes and risk factors.
