Regression Modeling Strategies Short Course 2026
The next 4-day course is planned for Thursday-Friday May 14-15 and Monday-Tuesday May 18-19, 2026. It is sponsored by the American Statistical Association and given through Instats.
Do you need
- A statistical modeling tune-up or to learn about modern flexible methods for developing and validating predictive models?
- To understand the advantages and disadvantages of machine learning relative to statistical models?
- To know the importance of causal inference in formulating models?
The only full Regression Modeling Strategies 4-day course offered this year covers a comprehensive strategy for developing accurate predictive models, model specification that preserves information, quantifying predictive accuracy, avoiding overfitting, data reduction (unsupervised learning), making optimum use of incomplete data, validation, the art of data analysis, comprehensive case studies, and more.
The RMS 4-day short course will be held as a virtual course on May 14-15 and 18-19, 2026. This will be a very interactive live web course using Zoom. Registration opens in mid March (see below). The course includes case studies using R.
Participants who wish to learn more about R, or to be refreshed in the prequisite regression knowledge for the 4-day course, may wish to register separately for the optional and auxiliary one-day Pre-RMS workshop on May 11 (see below) to enhance R and RStudio skills, learn about multiple linear regression (a prerequisite for the 4-day course), and to get an introduction to the R rms package.
R interactively.About the Course
Four-day Short Course in Regression Modeling Strategies by
Frank E. Harrell, Jr., Ph.D., Professor, Department of Biostatistics, Vanderbilt University School of Medicine, Instructor
Drew G. Levy, Ph.D., GoodScience Inc., Guest Instructor and Moderator
Target Audience
Statisticians and other quantitative researchers who want to learn some general predictive model development strategies, including approaches to missing data imputation, data reduction, model specification and variable selection, model validation, relaxing linearity assumptions, and how to choose between machine learning and statistical models.
Prerequisites
Good working knowledge of ordinary multiple regression models. Some individuals will want to take the free Biostatistics for Biomedical Research course in preparation (especially sessions on regression). Or take the 1-day workshop to learn the prequisites (concentrating on multiple linear regression) for the 4-day course.
Required pre-course study materials are here.
Details
Schedule
All times are U.S. Central Daylight Time (Chicago Time)
| Day | Date | Time | Description |
|---|---|---|---|
| Monday | May 11 | 9a-12p, 1p-4p | optional workshop on R and prerequisites |
| Thursday | May 14 | 9a-12p, 1p-4p | begin 4-day RMS course |
| Friday | May 15 | 9a-12p, 1p-4p | |
| Monday | May 18 | 9a-12p, 1p-4p | |
| Tuesday | May 19 | 9a-12p, 12:30p-3p | |
Registration Information for 4-Day Course
A registration link will appear here during the first week of March.
Registration opens in mid March and is expected to close on May 9. Please email interest/questions to fh@fharrell.com.
Course fees are paid through Instats.org at three levels
- Non-students
- Students
- Free enrollment for the following categories; email
fh@fharrell.comto provide the email address you will use to register atInstats- Full-time faculty and staff or current graduate students of the Vanderbilt University Department of Biostatistics with
vumc.orgorvanderbilt.eduemail addresses - Full-time staff of Baylor Scott & White Research Institute with
bswhealth.orgemail addresses - Members of the Nigeria-Vanderbilt Biostatistics Program
- Full-time faculty and staff or current graduate students of the Vanderbilt University Department of Biostatistics with
Pre-RMS: Introduction to R, RStudio, Regression, and the R rms Package
1-Day Workshop
Frank E. Harrell, Jr., Ph.D., Professor, Department of Biostatistics, Vanderbilt University School of Medicine, Instructor
Drew G. Levy, Ph.D., GoodScience Inc., Moderator
- For those new to R who want to learn about resources for taking your working knowledge of R to the next level (note that knowledge of R is not a prerequisite for the 4-day course but will make example code easier to understand).
- Also for those who have had some real exposure to statistics but who lack the regression model background for the 4-day course. The workshop introduces simple and multiple linear regression using material from Biostatistics for Biomedical Research.
- Learn how to use the R
rmspackage to make common tasks easy to do, e.g., relaxing linearity assumptions, getting useful statistical tests (including multiple degree of freedom “chunk” tests) and confidence intervals. - Get a quick introduction to Quarto for state-of-the-art reproducible statistical report construction.
- Get a quick introduction to some other components of R Workflow that help you in annotating datasets and achieving a high-efficiency analysis workflow.
- Course description
Course Fees for R Pre-RMS Workshop Monday May 12, 2025 9:00am - 4:30pm CDT
- Registration will be through Instats
- There are three categories of registration as defined above for the 4-day course
Materials
- 1-day Pre-course details
- Pre-course study for 4-day course
- Handouts
- Dr. Harrell’s Book - REGRESSION MODELING STRATEGIES with Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
- Causal Models for Variable Selection by Drew Griffin Levy
- Full semester course syllabus
- An introduction to the Harrell”verse” by Nicholas Ollberding
- Biostatistics for Biomedical Research
- R Workflow
This course is not under the auspices of Vanderbilt University.