When

The third edition of the RDA Winter School is being planned for November 2025!

Where

Stockholm, Sweden.

Course 1: To be announced

Dates: Monday – Tuesday

Schedule: 9am – 5pm

Course 2: Competing risks and multi-state models

Dates: Wednesday – Friday

Schedule: 9am – 5pm

Faculty

This 3-day course will provide an overview of principles, methods, and applications for competing risks and multi-state models.

Day 1: Competing risks

Day 2: Multi-state models I

Day3: Multi-state models II

What to expect

The course faculty have experience both developing statistical methods and applied clinical research. We expect the participants to have heterogeneous backgrounds (including statisticians, epidemiologists, and clinicians) and to have considerable knowledge and experience to complement that of the faculty. The course will include lectures on key topics, which we hope will be of interest to all participants. Our aim is for the teaching to be participant-centered, and we will devote considerable time to practical sessions where a large faculty will be on hand to provide individual (or small-group) instruction in the areas of specific interest to participants. We ask that participants state their areas of interest on the course application form, and we will do our best to provide tailored instruction with a suitably qualified faculty member. We are happy to discuss your ongoing research projects with you during the course, whether they be development of methods or application of methods. Bring your data with you if you can!

Computing

The primary software for the course will be Stata, with support for Stata version 17 or higher. A temporary Stata license can be provided on request when you register. Participants are welcome to use R instead, with full support and materials available. Please state your chosen software in the course registration so we can prepare. We are happy to discuss concepts and methods with participants who use other software, but we can’t promise software-specific expertise.

Who should attend?

Epidemiologists, statisticians, physicians, public health specialists or anyone with an interest in advanced survival analysis. The methods we teach can be applied to any area. The course faculty have their formal training in mathematics and statistics but devote a large proportion of their time to applied clinical research. The primary target audience is researchers, irrespective of background.

Expected prior knowledge

We expect participants to possess basic knowledge of the fundamentals of epidemiology and biostatistics and be comfortable fitting statistical models in epidemiology (e.g., logistic regression, Poisson regression, or Cox regression). Based on experience, we know that participants will have a wide range of backgrounds. Some of the content will be directed at those with formal training in statistics, but the main emphasis of the course will be on concepts and application with a minimum of complex mathematical detail. Participants will gain most if they have some previous knowledge of basic concepts in survival analysis such as survival functions, Kaplan-Meier curves, and Cox regression.

Register your place

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