Graduate School of health and Medical Sciences

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

Activity no.: 3319-18-00-00
	Enrollment deadline: 24/10/2018

Date and time	20.11.2018, at: 00:00 - 07.12.2018, at: 00:00
Regular seats	75
Course fee	2,280.00 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). All other participants must pay the course fee. Aim and study 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, reproducibility of measurement methods, multi-level analyses. • Perform your own analyses using SAS (or 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 design. 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 one different locations of the body, or when observations are clustered as from patients in a multi-center randomized trial or pups belonging to the same litter. Pitfalls of traditional statistical analyses will be discussed and appropriate models for analysis will be exemplified. Topics include longitudinal data analysis, baseline follow-up studies, cross-over trials, reproducibility of measurements methods, and multi-level models. A thorough introduction to linear mixed models for quantitative outcomes will be given, while generalized linear mixed models and generalized estimating equations for the analysis of binary, ordinal, and count data is more briefly introduced by the end of the course. Lectures include examples of statistical analyses performed with SAS statistical software and computer exercises with SAS/R will be given. Statistical software You must bring your own labtop with SAS or other appropriate software installed to participate in the exercises. Supplementary R material and R solutions to all exercises are available. If you prefer to use SPSS or Stata you are free to do so, but cannot expect much support from the teachers. Textbook Most 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. Participants Ph.D.-students with a basic knowledge of statistics, e.g. corresponding to the course “Basic statistics for health researchers”. In case of vacant seats also other health researchers. Max. 75 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 Lene Theil Skovgaard and others. Course secretary Susanne Kragskov Laupstad, Department of Biostatistics, e-mail: skl@sund.ku.dk Dates 20, 23, 27 and 30 November and 4, 7 December 2018, Tuesdays 12-18, Fridays 8-15. Course location CSS Registration: Please register before 24 October 2018 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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