Listwisemenetelmän

Listwisemenetelmän is a Finnish term that translates to "list-wise deletion" in English. It refers to a method used in statistical analysis, particularly in the context of dealing with missing data in datasets. This technique involves analyzing complete cases only, meaning that any observation (row) that contains at least one missing value for any of the variables being analyzed is completely excluded from the analysis.

The primary advantage of list-wise deletion is its simplicity. It requires no complex imputation methods and results in a dataset that is easy to work with. The analysis is performed on a consistent subset of the data, ensuring that all statistical calculations are based on the same set of variables. This can be particularly appealing when the proportion of missing data is small.

However, list-wise deletion can significantly reduce the sample size if missing data is prevalent. This reduction in sample size can lead to a loss of statistical power, making it harder to detect significant effects. Furthermore, if the missing data are not randomly distributed, list-wise deletion can introduce bias into the analysis. For example, if individuals with certain characteristics are more likely to have missing data, excluding them entirely from the analysis will result in a sample that is not representative of the population. Therefore, while simple, it is often considered a less desirable method when compared to more sophisticated techniques for handling missing data, especially if the missingness is substantial or systematic.