Course catalogue doctoral education - VT18

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Title Longitudinal data analysis - classical and modern statistical methods
Course number 2858
Program 0-Inte del av forskarutbildningsprogram
Language English
Credits 3.0
Date 2017-10-23 -- 2017-11-10
Responsible KI department Institutionen för lärande, informatik, management och etik
Specific entry requirements Basic medical statistics (or equivalent)
Purpose of the course The aim of the course is to introduce statistical models and methods for the analysis of longitudinal data and to develop statistical skills of analyzing dependent data.
Learning outcomes After successful completion of the course the student will be able to: 1. Understand the underlying characteristics of longitudinal data 2. Identify appropriate tests for longitudinal studies 3. Manage longitudinal datasets and prepare these for statistical analysis using statistical software program SPSS 4. Apply both simple and complex statistical methods of longitudinal data 5. Use SPSS to perform the above mentioned statistical analysis 6. Present and interpret the results of analysis.
Contents of the course The main focus will be on frequently used statistical methods and how these should be used to provide more insight concerning research questions in longitudinal studies. Thus the course covers both classical and modern methods to analyze longitudinal data. Topics include Univariate repeated measures analysis of variance, Multivariate repeated measures analysis of variance, Drawbacks and limitations of classical methods; General linear models for longitudinal data; Linear mixed effects models. The underlying mathematical theory will not be stressed, and the main focus will be on concepts and applications.
Teaching and learning activities Teaching methods include lectures, computer based exercise and seminars. Participants will have access to materials from a number of studies and are given the opportunity to use the statistical software program, SPSS during practice sessions. In addition, you will have seminars, group discussion and presentations.
Compulsory elements Computer based exercises, seminars, presentations and some lectures are mandatory. The course leader assesses whether and if so, how absence can be compensated.
Examination Assessment of attainment of the intended learning outcomes by a passing grade on the computer based exercises, and the performance during the final seminar.
Literature and other teaching material Robert E. Weiss: Modeling Longitudinal Data: Linear, Logistic, Survival, and Repeated Measures Models, Second edition, Springer, 2012. Garrett M. Fitzmaurice et al.: Applied Longitudinal Analysis 2nd edition Wiley 2011 Betty R. Kirkwood & Jonathan A.C. Sterne Essential medical statistics, 2nd edition, Blackwell 2003
Number of students 18 - 20
Selection of students Selection will be based on 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) date for registration as a doctoral student (priority given to earlier registration date).
More information The course will consist of four scheduled full days per week for two weeks (week 43 & 45). Course dates: October 23-24, 26-27 & November 6-7, 9-10.
Additional course leader
Earlier evaluation of the course Evaluation report
Course responsible Mesfin Tessma
Institutionen för lärande, informatik, management och etik

Mesfin.Tessma@ki.se
Contact person Elisabeth Löfgren
Institutionen för lärande, informatik, management och etik

elisabeth.lofgren@ki.se