Missing data analysis and multiple imputation

Few missing values are universal accompanier of data in every research. However, missing value load exceeding 5% of total data burden of that variable will signal alarm. There are two key types of missing data: a) Missing is unpredictable and random: Non-response in data outcomes is randomly distributed and cannot be attributed to any unobserved or observable factor in the study & b) Missing is systematic and predictable: Here certain cause (observed or unobserved) can be assigned to missing values.