Training courses
Internationally recognised short courses and schools on survival analysis, joint modelling, competing risks, multi-state, longitudinal, and causal-inference methods — taught by the people who develop the methods and the software.
Our courses combine statistical theory with hands-on practicals. Most run online as short courses through the year; we also teach at international schools and have hosted the RDA Winter School in Stockholm. The primary software is Stata, with full R solutions provided throughout.
Looking for bespoke in-house training scoped to your team? Typically 5 to 15 people over one or two days, online or on-site, shaped around the methods and the data your team actually works with, and quoted per engagement rather than per seat. Allow four to six weeks from agreeing the scope to teaching it. Get in touch and we'll design something around what you need.
Short courses
One-day to three-session online courses. Each runs two to three times a year, and dates are announced around three months ahead. Go on the register → and you hear about a course you want before the date is public.
Survival analysis
An introduction to the core concepts, methods, and software of time-to-event analysis — for beginners in survival analysis.
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Flexible parametric survival analysis
Royston-Parmar flexible parametric models as an alternative to Cox regression — flexible baseline hazards with straightforward, interpretable predictions.
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Competing risks
A comprehensive introduction to competing-risks models for predicting absolute risks of disease and prognosis from time-to-event data.
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Multi-state survival analysis
An introduction to the concepts, methods, and software of multi-state survival analysis — modelling complex disease pathways and the transitions between states.
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Joint modelling of longitudinal and survival data
An introduction to the concepts, methods, and software of joint models — linking repeatedly measured biomarkers with time-to-event outcomes.
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Longitudinal analysis
Analysing repeated measurements collected over time — quantifying change in a response and the factors that drive it, with a focus on mixed-effects models.
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Multilevel survival analysis
An introduction to the concepts, methods, and software of multilevel (hierarchical) survival analysis — time-to-event data where individuals are nested within clusters.
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Multi-day, in-person and partner schools — including the annual RDA Winter School in Stockholm and courses we teach at international summer and winter schools.
Summer School: Joint modelling of longitudinal and survival data
A week-long summer-school course on joint modelling of longitudinal and survival data, with real applications to clinical-trial data and electronic health records.
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Swiss Epidemiology Winter School: Competing risks & multi-state models
A Swiss Epidemiology Winter School course on competing risks and multi-state models, built on flexible parametric survival models with restricted cubic splines.
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RDA Winter School 2025
The third edition of the RDA Winter School in Stockholm — two concurrent courses on causal inference in survival analysis and on competing risks & multi-state models.
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RDA Winter School 2024
The second edition of the RDA Winter School in Stockholm — population-based cancer survival analysis, and joint modelling of longitudinal and survival data.
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RDA Winter School 2023
The first RDA Winter School in Stockholm — a five-day intensive across flexible parametric survival, competing risks, multi-state models, and joint modelling.
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