Multiple imputation analysis of Miettinen-Nurminen for binary endpoints

Music City Center 

Cochran-Mantel-Haenszel (CMH) and Miettinen-Nurminen (MN) methods are widely used in comparing the proportions among treatment groups in clinical trial data analysis. When missing data exists, multiple imputation (MI) can be used for dealing with the missingness. CMH method with Rubin's rule are commonly used for estimating the confidence interval (CI) and hypothesis testing, when MI is used for missing data. Previous publications have proposed an approach to estimate CIs using MN with MI for missing data. However, the algorithm of estimating the CI and hypothesis testing for MN method with MI at the same time is not available. In addition, the difference of performance between proposed the MN method and the CMH method with Rubin's rule remain unexplored. In this study, we extended the algorithm of MN method with MI and demonstrated the comparable performance of proposed MN method with CMH method using comprehensive simulations.

Missing data

Multiple imputation

Binary endpoints

Miettinen-Nurminen Method

Cochran-Mantel-Haenszel Method 

Biopharmaceutical Section