Dr Corrie Macdonald-Wallis (course organiser), Prof Kate Tilling, Dr Andrew Wills, and Dr Abigail Fraser
10 December 2013
The aim of the course is to introduce several statistical methods that can be used to analyse longitudinal data in lifecourse epidemiological studies.
By the end of the course, students will be able to:
The course is intended for researchers who are, or will be, involved in life course epidemiology research. The focus of this course is on the relative strengths and limitations of different statistical analysis approaches for longitudinal data, the interpretation of results, and the types of research question that can be addressed with each method. No computer-based statistical analysis practical sessions will take place, so no knowledge of any specific statistical software packages is assumed. However, participants should be familiar with standard regression models for continuous and binary outcomes (to the standard of the short course "Introduction to Linear and Logistic Regression Models").
Topics to be covered include:
Teaching time is 7 hours. This will include interactive lectures and problem-based practicals (not computer-based practicals).
There is no required pre-course reading. However, students may be interested to read the following paper for a discussion of the types of statistical issues faced in lifecourse epidemiology:
De Stavola BL. et al. Am J Epidemiol. 2006; 163(1): 84-96
Please note: this course provides a general introduction to several statistical methods used in lifecourse epidemiology. Tuition on carrying out the analysis within statistical software packages is not provided on this course. Students wishing to learn how to conduct multilevel modelling (within Stata/MLwiN) and structural equation growth modelling (within Mplus) should also attend the ‘Analysis of Repeated Measures’ course.
For further information please contact firstname.lastname@example.org.