Graduate School of health and Medical Sciences

CANCELLED DUE TO COVID-19 - Bayesian statistical modeling using R-INLA
Provider: Faculty of Health and Medical Sciences

Activity no.: 3337-20-00-00
	Enrollment deadline: 17/04/2020

Date and time	18.05.2020, at: 08:00 - 20.05.2020, at: 12:00
Regular seats	15
Course fee	3,240.00 kr.
Lecturers	Torben Martinussen
ECTS credits	1.80

Contact person	Susanne Kragskov Laupstad E-mail address: skl@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee. Learning objectives A student who has met the objectives of the course will be able to: 1.Use Bayesian hierarchical models to do statistical inference. 2. Choose appropriate statistical models for various real data problems. 3.Perform statistical analysis of challenging datasets. 4. Use INLA as an approximate Bayesian inference method 5. Use R-INLA software. Content The Integrated Nested Laplace Approximation (INLA) method introduced by Rue et al. (2009) is an approximate method to perform full Bayesian inference efficiently and accurately. We will provide a basic overview of the INLA method as well as hands-on practical examples using the R-INLA software. R-INLA can perform inference for complex models with huge datasets. Some topics to be covered are generalized linear models, nonlinear covariates (spline models), time series models, survival models and also joint models. We will focus on applications and data for biostatistics. Participants Participants using statistical models for inference and/or prediction will benefit from this course. A basic knowledge of statisticalmodeling of data is necessary., i.e. general linear models, generalized linear models, Bayesian elements like priors and posterior etc. Competency in R will be beneficial. Max 15 participants. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Language English. Form Lectures and tutorials. Course director Professor Torben Martinussen, Section of Biostatistics. Teachers Prof. Haavard Rue, KAUST Dr. Janet van Niekerk, KAUST Dates 18-20 May 2020. 18 and 19 May from 8-15, 20 May from 8-12 Course location Center for Sundhed og Samfund (CSS), Øster Farimagsgade 5, 1353 København K Registration Please register before 17 April 2020. Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Application from other participants will be consideres after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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