Navigating the Pitfalls of MICE Algorithms: A Comparative Evaluation of Missing Data Analytical Methods

While multivariate imputation by chained equations (MICE) methods are widely applied to handle missing data, different algorithms may lead to inconsistent results. We systematically evaluated the performance of MICE algorithms, compared that with FIML and listwise deletion, and concluded that imputation algorithm selection is impactful and should be carefully determined.