There are several methods to handle MAR in pediatric research:
Multiple Imputation: This technique involves creating multiple datasets by imputing the missing values based on the observed data. The results from these datasets are then combined to produce final estimates. Maximum Likelihood: This method estimates the parameters of a statistical model that maximize the likelihood of the observed data, considering the missing data mechanism. Inverse Probability Weighting: This technique assigns weights to the observed data based on the probability of being missing, which helps to adjust for the missingness.
