Modern high-dimensional statistical inference often faces the problem of missing data. In recent decades, many studies have focused on this topic and provided strategies including complete-sample anal
Supplementary materials to: Fitzgerald, C. E., Estabrook, R., Martin, D. P., Brandmaier, A. M., & von Oerzen, T. (2021). Correcting the bias of the Root Mean Squared Error of Approximation under missi
Share repurchase is not only an important financial policy of the company, but also a financial policy with a very wide range of influence. A scientific and reasonable share repurchase policy has a si
Missing data is a common problem in general applied studies, and specially in clinical trials. For implementing sensitivity analysis, several multiple imputation methods exist, like sequential imputat
Missing data, a common issue in production processes due to factors like sample contamination and equipment malfunctions, can lead to a decrease in the recognition accuracy of control charts, especial