Graduate School of health and Medical Sciences

Statistical analysis of repeated measurements and clustered data
Provider: Faculty of Health and Medical Sciences

Activity no.: 3319-24-00-00
	Enrollment deadline: 12/04/2024

Date and time	14.05.2024, at: 08:00 - 31.05.2024, at: 15:00
Regular seats	90
Course fee	3,960.00 kr.
Lecturers	Julie Forman
ECTS credits	4.20

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 NorDoc member faculties. All other participants must pay the course fee. Learning objectives This advanced statistics course will give you and introduction to the most common repeated measurement designs used in medical research. The aim of the course is to teach you to: • understand and interpret the analyses of various repeated measurement designs including baseline follow-up studies, cross-over trials, and reproducibility of measurement methods, as well as analyses of clustered designs (e.g. multi-level models), and of mixed type. • perform your own analyses using R statistical software. • use model diagnostics to assess the validity of your analyses. • make suitable presentations of the results from your analyses. • understand the statistical consequences of different kinds of study designs. Content This course is concerned with the analysis of correlated quantitative data arising e.g. when collecting data repeatedly on the same persons, animals, or tissue over time or on different locations of the body, or when observations are clustered as from patients in a multi-center study, siblings or pups belonging to the same litter. Appropriate statistical models for analysis will be exemplified and statistical errors arising with other frequently employed analyses will be discussed. Topics include analysis of baseline follow-up studies, longitudinal data analysis, multi-level and variance component models, analysis of cross-over trials, and reproducibility of measurements methods. We will further discuss the potential biases that occur due to missing data and statistical methods for handling these. A thorough introduction to linear mixed models for quantitative outcomes will be given, while generalized linear mixed models and marginal models (aka generalized estimating equations) for the analysis of binary, ordinal, and count data are more briefly touched upon by the end of the course. Computer exercises with R statistical software will be given. Statistical software You must bring your own labtop with R and R Studio installed to participate in the exercise classes. Note that if you have never used R before we strongly recommend that you complete a course on R programming before attending this course. Textbook Many of the analyses taught are covered by G.M. Fitzmaurice, N.M. Laird, & J.H. Ware. Applied Longitudinal Analysis, 2nd ed., John Wiley & Sons, 2011. You are not required to buy the book, but we recommend it. Note: Students at the University of Copenhagen have free access to the e-book through the Royal Library. Lecture notes and R-demos are available from the course webpage. Participants PhD-students with a basic knowledge of statistics, e.g. corresponding to the course “Basic statistics for health researchers” and R programming at beginner level. In case of vacant seats also other health researchers. Max. 60 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 6 full days with forum lectures and computer exercises. Course director Associate professor Julie Lyng Forman, Department of Biostatistics Teachers Associate professor Julie Lyng Forman, associate professor Brice Ozenne and others. Course secretary Susanne Kragskov Laupstad, Department of Biostatistics, e-mail: skl@sund.ku.dk Dates 14, 17, 21, 24, 28, 31 May 2024, all days 8-15. Course location CSS Registration Please register before 12 April 2024. 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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