Biostatistics, Epidemiology, and Research Design (BERD) Lunch and Learn Series

The Biostatistics, Epidemiology, and Research Design (BERD) groups at Wake Forest, Duke, and UNC are working together to share educational and training resources. The seminars are designed to provide researchers and aspiring researchers with tools and resources related to each of the BERD disciplines. The following seminars are shared across all three institutions. 

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Spring 2026

Topic

Speaker

Summary

1/21/26

Introduction and overview of the ImpResPAC Tool Louise Hull, PhD, Associate Professor in Implementation Science and Chloe Sweetnam
This session will provide an introduction on the Implementation Science Research Proposal Appraisal Criteria (ImpResPAC) tool. ImpResPAC is a quantitative appraisal tool used to evaluate the conceptual and methodological quality of implementation research proposals.
 2/4/26 Survival Analysis Methods
Mitchell Paukner, PhD, Assistant Professor in Biostatistics and Data Science
This session will present an introduction to survival analysis including fundamental statistical concepts and approaches for analyzing outcome data in the form of time-to-occurrence of an event.
 2/18/26 An Introduction to the Qualitative and Patient-Reported Outcomes Shared Resource (Q-PRO) Erin Sutfin, PhD, Professor in Social Sciences and Health Policy This session will introduce the Qualitative and Patient-Reported Outcomes Shared Resource and when and how to implement this methodology in your work.
 3/4/26 An Overview of Missing Data and Multiple Imputation
Clemontina A. Davenport, PhD, Assistant Professor in Biostatistics and Data Science
This session will introduce issues of missing data in clinical and public health research. Material covered will describe practical and valid approaches for addressing missing data and when to consider more rigorous approaches.
 3/18/26 Introduction to Electronic Health Record Data (EHR) Kristin Lenoir, PhD, Assistant Professor in Biostatistics and Data Science This session will discuss a broad range of topics for EHR data and issues to consider with its use. Material covered will include data structure, data harmonization, integration strategies, and approaches to validation and verification.
 4/1/26 Analysis of Repeated Measures and Clustered Data Michael E. Miller, PhD, Professor in Public Health Sciences When unique observations or data points are not independent of one another, analytic methods must account for this dependence. This session will introduce issues with correlated observations and approaches for analyzing repeated measures outcome data.
 4/15/26 Prepare and Organize Data for Collaboration Dave Kline, PhD, Associate Professor in Biostatistics and Data Science  Spreadsheets are basic, general tools for organizing data. Software, like Excel, has many features to aid in organization of data and calculation of values of interest. However, data that appear organized and clear within a spreadsheet may not translate well into statistical software. These issues can create headaches for the statistician on the project and lead to delays in the processing and analysis of the data. In this talk, we will discuss ways to efficiently organize data so that it is machine-readable by statistical software and reduces the potential for errors. 
 5/6/26 Introduction to Meta-analysis and Systematic Reviews  Kaidi Kang, PhD, Assistant Professor in Biostatistics and Data Science This session provides a foundational overview of meta-analysis and systematic reviews - a powerful statistical technique used to quantitatively integrate and synthesize findings across multiple studies addressing a similar research question. Designed for researchers new to the topic, this session will first introduce the concept of meta-analysis, outline its practical applications, and walk through the essential steps involved in conducting one. This session will also highlight some important considerations while starting meta-analysis to ensure its scientific and statistical rigor and reliability.