Research Design and Statistics Core

Robot in simulationResearch Design and Statistics Core

The Research Design and Statistics Core Team at Duke University School of NursingThe Research Design and Statistics Core:

  • Conducts methodological studies applicable to social, behavioral and health care research.
  • Provides statistical support for DUSON’s research through collaborating and consulting activities with faculty members, postdocs and graduate students.
  • Teaches graduate courses on research methods and statistics.

Evidence-based practice has become a common practice in health care, and evidence has to be revealed through data analysis. Our core can help DUSON’s research community:

  • Identify and develop appropriate analysis techniques.
  • Further inform DUSON researchers with advanced statistical methods for them to continue to foster innovative research so as to move DUSON’s research forward.
Statistical Collaboration and Consultation

Collaboration implies that statisticians and clients work together to make decisions regarding the design of studies, the collection and analysis of data and the presentation and dissemination of research findings. If you need statistical collaboration, please read the general guidelines and submit a statistical support request (accessed through CNR Research Tools).

Consultation implies that statisticians provide methodological and statistical advice and guidance to clients interested in making decisions regarding the design of studies, the collection and analysis of data and the presentation and dissemination of research findings. If you need statistical consultation, please attend a statistics lab session.

Research Design and Statistics Lab

The Research Design and Statistics Lab provides walk-in, ad hoc consultation related to research design and statistical analysis for DUSON faculty, students, postdocs and DUHS nurses for their research with regard to the following needs:

  • Questionnaire design
  • Measurement validation
  • Database design
  • Data management
  • Data analysis
  • Statistical software coding

The Lab is located in the Pearson Building, Room 3143. The hours are Mondays from 1:00 p.m. to 4:00 p.m. and Thursdays from 9:00 a.m. to 12:00 p.m. Walk-ins are welcome.

Core Activities
  • Methodological Research

    • Moderation and mediation

    • Survival analysis on competing risks data

    • Aging and longitudinal modeling

    • Psychometrics

    • Causal inference

    • Propensity score analysis

    • Dynamic Treatment Regime and SMART design

  • Statistical Support

    • Grant proposal preparation

    • Research design

    • Questionnaire construction

    • Measurement validation

    • Data analysis plan

    • Power analysis and sample size determination

    • Data management

    • Data analysis and statistical modeling

    • Manuscript preparation

  • Training & Education

    • PhD Program

      • N915 Measurement & Theory Practice

      • N911 Statistical Methods & Data Analysis

      • N903 General Linear Models

      • N904 Categorical Data Analysis

      • N905 Longitudinal Method & Analysis

      • N9XX Special Topics

    • DNP Program

      • N966 Quantitative Evaluation

    • MSN Program

      • Nurse as Scholar I

    • SAS workshops

  • Publications and presentations 

Research Design & Statistics Core Faculty & Staff

Qing Yang, PhD

Assistant Professor

Dr. Qing Yang joined DUSON in July, 2014. She received her BS in Mathematics from Beijing Institute Technology in China, MS and PhD in Biostatistics from University of California, Los Angeles. Dr. Yang’s statistical research expertise are on longitudinal data analysis and survival analysis. She recently becomes interested in dynamic treatment regime, SMART design, Mobile health data and EHR data analysis. As a biostatistician, she has extensive experience collaborating with researchers in different therapeutic areas, including smoking cessation, mental health, diabetes, cardiovascular disease, breast cancer and etc.

Phone: (919) 613-9768
Office: 4218 Interprofessional Education Building

Wei Pan, PhD

Associate Professor

Dr. Wei Pan is an Associate Professor and Faculty Lead for the Research Area of Excellence in Methods and Analytics at the Duke University School of Nursing. He received his PhD in Measurement and Quantitative Methods from Michigan State University in 2001 and his MS in Statistics from Fuzhou University in China in 1989. His research work focuses on causal inference and propensity score methods, multilevel and structural modeling, research synthesis and meta-analysis, measurement and evaluation, and their applications in the social, behavioral, and health sciences, such as substance abuse and symptom management. He has been involved in many research projects funded by federal agencies, such as the National Institutes of Health, the National Science Foundation, and the U.S. Department of Education. He has published numerous refereed journal articles on both methodological and applied research studies. His recently published book entitled "Propensity Score Analysis: Fundamentals and Developments" tackles both methodological and practical issues in propensity score analysis, a statistical technique for reducing selection bias so as to increase the validity of causal inference from non-randomized controlled trials or observational studies.

Phone: (919) 684-9324
Office: 4216 Interprofessional Education Building
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