Missing data in medical research studies can lead to biased results. A new method combining multiple imputation and inverse-probability weighting was developed to analyze data with missing values. This method showed better performance in terms of bias and efficiency compared to using either method alone. The results suggest that combining these two approaches can provide more accurate results in clinical trial data related to postpartum bleeding.