Listwise deletion is a method used in statistical analysis to handle missing data. When researchers encounter incomplete data sets, they may choose to exclude any participant or observation that has missing values on any variable. This means that only complete cases are analyzed, which can simplify the analysis but may also lead to a loss of valuable information. While listwise deletion can make data analysis easier, it has some drawbacks. It can reduce the sample size significantly, potentially leading to biased results if the missing data is not random. Therefore, researchers must carefully consider the implications of using this method.