Primary examples of the former are biomarkers or other patient parameters that are measured during follow-up, whereas for the latter examples include the time to relapse of the disease, time to re-operation or time to death.
This Joint Models for Longitudinal and Survival Data course from Erasmus University Rotterdam introduces a new type of statistical models that can be used to investigate the association structure between longitudinal and survival outcomes.
In terms of software, we will use R and illustrate how these models can be fitted using package JM and JMbayes.
Participants will be expected to bring their own laptop computers to the session, and to have recent versions of R
You can apply until:
Always verify the dates on the programme website.
Professional statisticians, epidemiologists and public health experts, working in applied environments where hierarchical modelling and survival analysis are key issues.
This programme may require students to demonstrate proficiency in English.
This course assumes knowledge of basic statistical concepts, such as standard statistical inference using maximum likelihood, and regression models. In addition, basic knowledge of R would be beneficial but is not required.
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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