Quantitative Training, Research & Analysis Core
QTRAC provides assistance to researchers at all stages of their careers in the Department of Family Medicine.
The Quantitative Training, Research and Analysis Core (QTRAC) aims to directly contribute to the research mission of Department of Family Medicine by assisting the departmental faculty in all tracks, trainees such as post-doctoral fellows, students/residents, and staff in quantitative research projects that support their professional development.
Specifically, QTRAC provides:
- Expertise for the overall development of internal and external grant proposals by crafting the plan for designing and testing the quantitative objectives
- Support in the acquisition and management of quantitative data for a research project that is generated from a funded proposal
- Analysis for funded and unfunded projects (as long as they support the departmental research mission) and assist in dissemination of the findings by collaborating on resulting manuscripts and conference presentations
- Training and mentorship to Department of Family Medicine faculty, students/residents, post-doctoral fellows, and staff
Contact
New Process: How to receive QTRAC support for your project
1. Request form submitted (bit.ly/QTRACform)
2. Form reviewed by QTRAC
3. Kickoff meeting with director, analyst, and investigator
4. Project start: Analyst and investigator work together until project completion.
QTRAC Team Members
Ananda Sen
Research Professor
Family Medicine and Program Associate
Family Medicine
Medical School
Dongru Chen
Statistician, Senior
Dongru Chen, M.S., a member of the Department of Family Medicine, specializes in applied statistics for clinical trials, surveys, and other health studies. She has expertise in the Statistical Analysis System (SAS), the R software system, and IBM SPSS.
Kalpana Das
Statistician Intermediate
Kalpana Das joined the Department of Family Medicine after completing her Master's degree in Biostatistics at the University of Michigan with high distinction in April 2025. She has experience supporting clinical and health services research, especially in predictive modeling, longitudinal methods, survival analysis, survey methods, and spatial statistics. She is proficient in the R and Python programs. She also holds a BS-MS in Mathematics and Statistics from IISER Kolkata, India.
Katie Grode
Administrative Assistant Sr.
Katie Grode is a member of the Department of Family Medicine. She assists with the processing of all incoming QTRAC requests and inquiries.
Amy Runyon
Senior Data Manager
Amy Runyon, a member of the Department of Family Medicine, has several years of experience in social science research, with a research interest in using evidence-based alternative therapies to treat psychological disorders particularly in trauma and depression. She has a Master's degree in Quantitative Psychology from Ball State University and graduated Summa Cum Laude. She is proficient in the R and SPSS programs and is adept in creating and maintaining databases in REDCAP.
