Quantitative Methods for HIV Researchers: Workshop Series

HIV/AIDS research is generating increasingly large and complex data sets. To analyze these data sets, we need the next generation of HIV/AIDS researchers to learn skills in data processing and statistical analysis, as well as increase collaboration with quantitative scientists such as statisticians, mathematicians, computer scientists and engineers. The curriculum will train HIV/AIDS researchers in the data science and statistics skills required to analyze multi-parameter data through a series of hands-on workshops

2025 – 2026 Workshop Series: Quantitative Methods for HIV Researchers

Registration is now open for Part II: Statistical Foundations and Predictive Modeling in Health Research Workshops!

       Mondays, 1/26/26 - 3/2/26

       1 - 3pm EST via Zoom

       Register by Monday, January 12, 2026

Register Here 

Overview

The Quantitative Methods for HIV/AIDS workshop series is designed to provide HIV researchers with a hands-on introduction to quantitative analyses both through simple and large, complex data sets. These NIH-funded workshops are open to graduate students, postdocs, medical fellows, staff, and faculty working in the HIV/AIDS field. Non-Duke-affiliated applicants are welcome.

Details

Each part of the series consists of six, virtual, once-a-week workshops held on Mondays (from 1 – 3PM through Zoom. 

• Part I workshops will teach reproducible research and R language skills along with an introduction to data analysis and study design. The seminars will be taught using RStudio. (Note: R knowledge is necessary for Part II- Statistics Workshops and Part III- Assay Analysis Workshops).
  • There will be a Day 0: Introduction to R seminar for those with no prior experience in R. Participants with R experience may skip this session, but are welcome to attend.
• Part II workshops will build on the statistical concepts discussed in Part 1 and the utilization of predictive models using previously published HIV data. Attendees will learn important concepts in statistics and perform statistical analyses using real HIV data. We will introduce hypothesis testing, multiple testing correction, linear and logistic regression, and high dimensional modeling. The final session features a detailed walk-through of a real data example.
• Part III workshops will teach bioinformatics skills for analysis of high throughput sequencing datasets.

NOTE: The material presented in Part I is a pre-requisite for Part II and Part III. Participants fluent with R, RStudio, and Git may skip the Part I Workshops, but must understand that the material covered in Part I will not be reviewed in Part II and Part III. Part I seminars will be recorded for attendees unable to attend Part I but interested in Parts II/III. 

2025 – 2026 Workshops Schedule

Part I: Data Science Workshops (Mondays, 1 - 4pm EST)

9/29/2025       Introduction to R (*not a required workshop)

10/6/2025       Intro to Data Driven Research, Part 1

10/20/2025     Intro to Data Driven Research, Part 2

10/27/2025     Intro to Data Driven Research, Part 3

11/3/2025       Exploratory analysis and visualization, Part 1

11/10/2025      Exploratory analysis and visualization, Part 2

11/17/2025      Exploratory analysis and visualization, Part 3

 

Part II: Statistical Foundations and Predictive Modeling in Health Research Workshops (Mondays, 1 - 3pm EST)

1/26/2026       Hypotheses, non-parametric tests, power, and error

2/2/2026         Linear regression, categorical predictors, interaction effect

2/9/2026         Logistic regression and classification

2/16/2026       Penalized regression, cross-validation and overfitting

2/23/2026       Random forest and principal component regression

3/2/2026         Case study walk-through

 

Part III: Assays Workshops (Mondays, 1 - 3pm EST)

March - April 2026                 TBD