Simulation Study: Introduction of Imputation Methods for Missing Data in Longitudinal Analysis

Missing data are vital subject to perform a proper longitudinal analysis. Some just ignore and discard all missing data to have complete dataset. However, it can result in a very substantial loss of information. Therefore, it is important to comprehend imputation methods of handling missing data. This paper discusses four common imputation methods for longitudinal analysis. Then, using simulation…