ABSTRACT
In this chapter, the author addresses the missing value problem. Biased sampling due to missing cases can sometimes be mitigated by the covariate adjustment, while the methods for analyzing censored data. Many statistical procedures do not handle missing values explicitly. Case deletion will allow the readers to fit our chosen model, provided sufficient data remain after the missing value deletion. This method is also called complete case analysis because only complete cases are used in the model. Deleting missing cases is the simplest strategy for dealing with missing data. It avoids the complexity and possible biases introduced by the more sophisticated methods that the readers will discuss. If relatively few cases contain missing values, if deleting the missing cases still leaves a large dataset or if they wish to communicate a simple data analysis method, the deletion strategy is satisfactory.
