Guest Editors’ Introduction to the Special Section on Integrating and Analyzing Complex High-Dimensional Data in Social and Behavioral Sciences Research

The digital revolution has profoundly transformed the landscape of research in the social and behavioral sciences, driven in part by the emergence of novel forms of data such as process data, mobile sensing streams, and digital trace records.These data sources capture behavior in real time and at fine temporal resolution, often yielding datasets in which the number of variables far exceeds the number of participants-so-called high-dimension low-sample-size (HDLSS) data.At the same time, research paradigms have increasingly shifted toward multi-disciplinary approaches.Behavior and cognition are now studied not only from a psychological perspective, but also through environmental, social, clinical, and biomolecular lenses.This convergence has created both exciting opportunities for understanding psychological processes, but they also challenge the foundations of traditional statistical and psychometric modeling.