University of Pittsburgh logo

Apply Request Information

Dianxu Ren

MD, PhD
Director for Statistical and Data Support Services
Professor
Health & Community Systems

Profile

Dr. Ren is a Professor in the Department of Health & Community Systems at the School of Nursing, University of Pittsburgh. He also serves as the Director of Statistical and Data Support Services in the Office of Research & Scholarship (ORS) at the School of Nursing. In addition, he holds a secondary appointment as Professor in the Department of Biostatistics & Health Data Science at the School of Public Health, University of Pittsburgh. Dr. Ren is also a member of the Statistical Methodology Working Group at the University of Pittsburgh’s Alzheimer’s Disease Research Center (ADRC).

Scholarly Emphasis

Dr. Ren’s research interests include longitudinal data modeling, multilevel modeling, structural equation modeling (SEM), dyadic data analysis, and the application of novel statistical methods in the health sciences. He has served as a principal investigator and as a co-investigator/biostatistician on numerous research projects with both intramural and extramural funding. His independent research focuses on epidemiology and statistical methods in aging, gerontology, and Alzheimer’s disease–related dementias (ADRD), particularly through the use of large national databases. He has served on numerous bachelor’s, master’s, and PhD dissertation committees in both biostatistics and nursing. In addition, he has mentored predoctoral and postdoctoral fellows, as well as junior faculty, on their research projects and the application of advanced statistical methods.

Teaching

Dr. Ren teaches two graduate-level statistics courses for both on-site and online students at the School of Nursing: NUR2011: Applied Statistics for Evidence-Based Practice and NUR3032: Data Analysis for DNP Projects. These courses cover a range of topics, including basic statistics, ANCOVA, linear regression, logistic regression, longitudinal data analysis, and meta-analysis. Students also gain hands-on experience with statistical software to support practical application of the concepts.