Implementing MI typically involves the following steps:
1. Choose Software: Use statistical software like R, SAS, SPSS, or Stata that supports MI. 2. Identify Missing Data Patterns: Examine the data to understand the pattern and extent of missingness. 3. Specify the Imputation Model: Select appropriate variables and methods for imputation, considering the type of data (e.g., continuous, categorical). 4. Generate Imputed Datasets: Create multiple imputed datasets using the chosen software. 5. Analyze Each Dataset: Perform the desired statistical analysis on each imputed dataset. 6. Pool Results: Combine the results from the multiple analyses to obtain final estimates.
