Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, w

This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate est

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developme

Find guidance on using SAS for multiple imputation and solving common missing data issues. Multiple Imputation of Missing Data Using SAS provides both theoretic

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach