Dr. Mengli Xiao is a research assistant professor in the Department of Biostatistics & Informatics and a faculty member at the Center for Innovative Design & Analysis (CIDA). Her methodological research interests include meta-analysis, data integration, data heterogeneity and replicability, and statistical learning. She is particularly interested in collaborative research that uses clinical trials and real-world evidence to improve healthcare quality and equity.
Areas of Expertise
- Meta-analysis
- Data Integration
- Causal Inference
- Observational Studies
- Bayesian Inference
Education, Licensure & Certifications
- PhD, Biostatistics, University of Minnesota-Twin Cities, 2022
- MS, Biostatistics, University of Minnesota-Twin Cities, 2018.
Awards
- ENAR Distinguished Student Paper Award, International Biometric Society, 2022.
Research
- Xiao, M., Chu, H., Hodges, J. S., & Lin, L. (2024). Quantifying replicability of multiple studies in a meta-analysis. The Annals of Applied Statistics, 18(1), 664-682
- Wang, Z., Murray, T. A., Xiao, M., Lin, L., Alemayehu, D., & Chu, H. (2023). Bayesian hierarchical models incorporating study‐level covariates for multivariate meta‐analysis of diagnostic tests without a gold standard with application to COVID‐19. Statistics in Medicine, 42(28), 5085-5099
- Xiao M, Chu H, Cole SR, Chen Y, MacLehose RF, Richardson DB, Greenland S (2022). Controversy and Debate: Questionable utility of the relative risk in clinical research: Paper 4: Odds Ratios are far from "portable" - A call to use realistic models for effect variation in meta-analysis. J Clin Epidemiol, 142:294-304
- Xiao M, Lin L, Hodges JS, Xu C, Chu H (2021). Double-zero-event studies matter: A re-evaluation of physical distancing, face masks, and eye protection for preventing person-to-person transmission of COVID-19 and its policy impact. J Clin Epidemiol, 133:158-160
- Xiao M, Shen X, Pan W (2019). Application of deep convolutional neural networks in classification of protein subcellular localization with microscopy images. Genet Epidemiol, 43(3):330-341.
- Gutama B, Wothe JK, Xiao M, Hackman D, Chu H, Rickard J (2022). Splenectomy versus Imaging-Guided Percutaneous Drainage for Splenic Abscess: A Systematic Review and Meta-Analysis. Surg Infect (Larchmt), 23(5):417-429.
