I am an Associate Professor in the Department of Biostatistics and Bioinformatics at Duke University. I am also affiliated with the Duke Clinical Research Institute and the Duke Center for REACH Equity.

My methodological research focuses on nonparametric, semiparametric, and causal inference methods for comparative effectiveness studies, clinical trials affected by non-compliance, not-so-perfect experiments, and observational studies. My goal is to develop statistical methods that make the best use of the data collected to answer scientific questions while applying principled methods to minimize bias and ensure fair assessments.

The substantive areas of application of my research include public health, biomedical, and social sciences.   As a DCRI faculty statistician, I collaborate with clinical researchers to better understand and treat cardiovascular diseases. I am actively involved in the analyses of large registry data including the Society of Thoracic Surgeons (STS) National Database, the STS and American College of Cardiology (ACC) Transcatheter Valve Therapy (TVTR) Registry, and the American Heart Association/American Stroke Association Get With The Guidelines (GTWG).

I am also a member of the Duke Center REACH Equity Measures, Methods, and Analysis Subcore.  The overarching goal of REACH Equity is to develop and test interventions that reduce racial and ethnic disparities in health by improving the quality of patient-centered care in the clinical encounter across settings, diagnoses, stages of illness, and throughout the life course.  At REACH Equity, my function is to ensure the conduct of rigorous, reproducible, synergistic research related to the Center’s theme. In that regard, I  advise clinical investigators and provide analytic and data management support for research projects conducted by the Center.

Finally, I lead the analytic team for the Consortium for the Holistic Assessment of Risk in Transplant (CHART). Our mission is to impart foundational change throughout the entire transplant  selection process, by assessing how we collect, organize, and use data to determine patient eligibility for transplant. This multi-center and multi-dimensional health system data goal is to identify and characterize center and system level drivers of inequities in access to transplant (across multiple domains), in order to effectively design interventions that improve equity in access to transplant.

Research Interests:

Causal Inference; Clinical Trials; Comparative Effectiveness.
Statistical and Epidemiological Methods.
Nonparametric statistics and Semi-Parametric Models.
 Survival analysis; Composite and Prioritized Outcomes.
Longitudinal, Multicenter, and Multilevel Data;
Registry and Observational Data; Health Services Research.


Roland A. Matsouaka, PhD
Department of Biostatistics and Bioinformatics
& Duke Clinical Research Institute
300 W. Morgan Street, Durham, NC 27701
Email: roland.matsouaka@duke.edu
Phone: (919) 668 7838