Missing data can introduce bias and error, threatening the accurate interpretation of test scores. The presenter will review the threats of missing data to the accuracy of parameters and standards errors as well as strategies for appropriate handling it. Expressly, the presenter will discuss the importance of assessing the missingness mechanism and level of missing to accurately select the appropriate deletion or imputation procedure.
