The process of multiple imputation generally involves three steps: 1. Imputation: Generate multiple (e.g., 5-10) complete datasets by replacing missing values with plausible data points based on observed data. 2. Analysis: Perform standard statistical analysis on each of these imputed datasets. 3. Pooling: Combine the results from these analyses to produce a single set of estimates and standard errors that reflect the uncertainty due to missing data.
