Missing data can derail even the most promising analysis, but modern imputation techniques are transforming this challenge into a solvable problem. From straightforward substitutions to advanced ...

Missing data imputation is a critical process in data analysis, enabling researchers to infer plausible values for absent observations. Over recent decades, a variety of methods have emerged, ranging ...