Craig Enders

Missing data are a nearly universal problem for applied researchers, particularly within educational settings where missed responses or losses of participants from a study are common occurrences. Although there are numerous and diverse strategies to address missing data, researchers often use a small collection of strategies (e.g., regression imputation, listwise deletion) that are outdated and inappropriate. The purpose of the current project is to provide researchers with clear research-ba...

Missing data are exceedingly common in educational research. Education research studies have missing data because students opt out of achievement testing, skip test items, or move to a different school district, among many other reasons. A previous IES award funded the development of a data analysis application, called Blimp, that addresses this issue by filling in missing values using sophisticated predictive models. The purpose of the current work was twofold: expand Blimp's missing data i...