Listwise deletion

Because listwise deletion excludes data with missing values, it reduces the sample which is being statistically analysed.

Listwise deletion is also problematic when the reason for missing data may not be random (i.e., questions in questionnaires aiming to extract sensitive information.

For instance, a questionnaire may include questions about respondents drug use history, current earnings, or sexual persuasions.

Multiple imputation is an alternate technique for dealing with missing data that attempts to eliminate this bias.

While listwise deletion does have its problems, it is preferable to many other methods for handling missing data.