Missing data imputation is a critical process in data analysis, enabling researchers to infer plausible values for absent observations. Over recent decades, a variety of methods have emerged, ranging ...

Data is almost always incomplete. Patients drop out of clinical trials and survey respondents skip questions; schools fail to report scores, and governments ignore elements of their economies. When ...

In longitudinal clinical trials, missing data is a threat to scientific integrity. Whether due to patient dropouts, missed visits, or protocol deviations, these gaps can distort results, reduce ...

Haewon Jeong, an assistant professor in UC Santa Barbara’s Electrical and Computer Engineering (ECE) Department, experienced a pivotal moment in her academic career when she was a postdoctoral fellow ...