Graduate School of health and Medical Sciences

Targeted Register Analysis
Provider: Faculty of Health and Medical Sciences

Activity no.: 3351-23-00-00
	Enrollment deadline: 20/11/2023

Date and time	11.12.2023, at: 08:00 - 14.12.2023, at: 15:00
Regular seats	50
Course fee	3,360.00 kr.
Lecturers	Thomas Gerds
ECTS credits	2.80

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

Enrolment Handling/Course Organiser	PhD administration SUND 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 NorDoc member universities. 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. understand the limitations of logistic regression and Cox regression 2. know how to ask causible questions (target parameters) before looking into the register data 3. define dynamic treatment regimens and analyse register data using the R-package ltmle 4. have knowledge of statistical (machine) learning algorithms for register data 5. use the R-package targets to setup and organize a reproducible analysis Content The course consists of 4 days where each day consists of lectures about methods and exercises with R: Lectures: International experts are giving lectures about recent developments in statistical methods for register analyses. The aim is inspiration and the lectures should be about methods that are as complex as they have to be to solve the real world problems; they should neither simplify the data nor the methods only for the sake of teaching success. The tentative list of topics is: • Analysing Danish register data • The roadmap of targeted statistical learning • The transition from traditional epidemiological tools (cohort followup studies, case-control studies) which produce hazard ratios or odds ratios to average treatment effects defined in a dynamic causal framework • Machine learning (random forests/recursive neural networks) • Longitudinal minimum loss estimation (LTMLE) Exercises: Participants learn data management with R, especially with respect to working with data from Danish registers. During the computer exercises participants will learn how to move a given data analysis project from the often encountered situation of a messy 1-room appartment to a functional multiroom laboratory that invites collaborators to follow the workflow. All steps of the analysis, from the import of the raw data until the export of the tables and figures are controlled by the R-package targets. Participants The course is tailored for Ph.D.-students in health sciences who already have taken the Ph.D.-course ``Basic Statistics for Health Researchers'' or have a similar knowledge about statistics, and who wish to have more knowledge about the statistical methods underlying the approaches presented in the course. A basic knowledge of programming with R is expected and previous experience with register data analysis is a great advantage 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 The course will consist of 4 days lectures and exercises. Course director Thomas Gerds, Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen, tag@biostat.ku.dk Teachers Christian Torp-Pedersen, Nothern Sealands Hospital and Section of Biostatistics, Department of Public Health, University of Copenhagen Marvin Wright, Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany Edwin Fong, University of Hongkong Andrew Mertens, postdoc, Division of Biostatistics ,University of California, Berkeley Thomas A. Gerds, Section of Biostatistics, Department of Public Health, University of Copenhagen Dates 11, 12, 13, 14 December 2023, all days 8.00-15.00 Course location CSS Registration Please register before 20 November 2023 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered 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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