معرفی
Fan Jia is an Assistant Professor in the Department of Psychological Sciences at the University of California Merced. Her research focuses on advanced statistical methodologies for handling complex data structures, particularly in developmental psychology and educational research. She specializes in missing data analysis, latent variable modeling, and growth trajectory analysis.
Her work emphasizes Bayesian approaches to model misspecification detection, longitudinal data analysis, and methodological comparisons of imputation strategies. She applies these techniques to real-world problems in education, public health, and developmental assessment, such as evaluating autism intervention programs and analyzing disparities in substance use patterns among Asian American populations.
Dr. Jia has contributed to the development of efficient measurement tools for early childhood progress monitoring and has explored innovations in data-driven decision-making for educational interventions. Her research bridges theoretical statistical advancements with practical applications in developmental science and policy.
