What is the method called that deletes an entire case with a missing variable from all analyses involving that variable?

Listwise deletion is a method used in statistical analyses where any case (or participant) that has a missing value for any of the variables involved in the analysis is completely removed from all calculations. This approach ensures that every case included in the analysis has complete data for all variables, thus maintaining the integrity of the analysis by avoiding the introduction of biases or distortions that could arise from handling missing data in other ways.

This method is particularly beneficial when the amount of missing data is relatively small, as it keeps the analysis straightforward and preserves the relationships between the variables. It also simplifies the interpretation of the results because every participant analyzed contributed complete and relevant data. However, it is important to note that if a large portion of data is missing, using listwise deletion could lead to a significant reduction in the sample size and potentially compromise the statistical power of the analysis.

In contrast, other methods, like pairwise deletion, involve excluding cases from analyses only when they lack specific variables, which can lead to different sample sizes for different analyses. Predictive replacement refers to using statistical techniques to estimate missing values rather than deleting them, while data validation pertains more to ensuring data accuracy and integrity rather than addressing missing data directly.