Missing data in medical research can skew results and reduce accuracy. Imputation methods can estimate missing values, with multiple imputation being a reliable approach. This method assumes missing data are random and helps improve the efficiency and reliability of estimates by making the most of available data. Imputation does not fix poor-quality data but can enhance the accuracy of reconstructed measurements.