Raffaele Vardavas

Semantic Embedding and Synthetic Augmentation for Longitudinal Survey Prediction (Student Abstract)

Longitudinal surveys are a crucial component of behavioral research. Such surveys, however, face significant gaps in the data created by item and unit non-responses as well as semantic gaps resulting from questionnaires, assessed trends, and data collection methods evolving over time. Using 15 waves