Topics covered during the Institute include:
- Basic probability and statistical inference
- Regression analysis, including linear and logistic regression, with applications such as survival analysis and risk predication
- Research ethics and human subjects protections
- Functional data analysis
- Causal inference
- Time-to-event data and staggered study entry
- Machine learning
- Clinical trials
- Personalized medicine
- Use of electronic health records and patient reported data in research
On most days (Mon-Fri), instruction will be delivered in multiple formats, including lectures, special presentations, group panel discussions, and “hands-on” activities where students learn to use statistical software for data analyses and computer simulation exercises. There will typically be two instruction sessions each day: one in the morning from 10am-12pm ET and one in the afternoon from 1:30-3:30 ET.
Each week will feature a field trip related to issues of importance to biostatistics.
Following common statistical practice, students will be randomized into teams of 2-3. During the last week of the program, these teams will apply the techniques learned in class to analyze the data in a hack-a-thon style (friendly) competition. Teams will present their results during the last Thursday of the program. To allow students to get to know each other, teams will be rotated twice during the program.