Bridging Advanced Quantitative Methods and Applied Research in the Behavioral, Social and Health Sciences
Missing data are a common problem faced by nearly all data analysts, particularly with the increasing emphasis on the collection of repeated assessments over time. Data values can be missing for a variety of reasons. A common situation is when a subject provides data at one time point but fails to provide data at a later time point; this is sometimes called attrition. However, data can also be missing within a single administration. For example, a subject might find a question objectionable and not want to provide a response; a subject might be fatigued or not invested in the study and skip an entire section; or there might be some mechanical failure where data are not recorded or items are inadvertently not presented. Regardless of source, it is very common for assessments to be missing for a portion of the sample under study. Fortunately, there are several excellent options available that allow us to retain cases that only provide partial data.