Analysis of Repeated Measures

Course dates

6-8 March 2017.

Course duration: 3 days (approximately 17 hours teaching, including introductory talks, lectures, worked examples and practical sessions using both Stata and Mplus software package. Approximately 40% of the course will be practical work).
Registration will begin at 9.30am on the first day, the course will finish by 4pm on the final day.

Course tutors

Dr Jon Heron (course organiser) and others.

Course aims and objectives

This course provides an introduction to methods for analysing longitudinal/repeated continuous data, with a focus on methods for analysing individual trajectories over time. Multilevel modelling and structural equation modelling (SEM) approaches will be described and compared. Throughout the course there will be an emphasis on what kinds of research question different types of method can be used to explore and on the interpretation of results.

By the end of the course participants should be able to:

  • understand when and why repeated measures data require appropriate  analysis;
  • understand and be able to use linear and simple non-linear models for modelling trajectories of continuous outcomes;
  • check the fit of models for continuous outcomes;
  • understand and be able to apply latent class models for trajectories of continuous variables;
  • be able to critically appraise the reporting of the above methods in the literature.

Who the course is intended for

The course is intended for researchers who are, or will be, involved in analysing longitudinal data. Participants should be familiar with the algebra of standard regression models for continuous outcomes (to beyond the standard of the short course 'Introduction to Linear and Logistic Regression Models', or to the level implied by module 3 of the Centre for Multilevel Modelling's online multilevel modelling course.

Please note: This is an advanced-level course, which will introduce MLM and SEM models, plus practicals using two different software packages (Stata and Mplus), in three days. Please be aware that whilst we assume no previous experience of Mplus, this course may prove challenging for those who are not fairly fluent in Stata.

Course outline

  • Background: Why collect, and how to analyse longitudinal data?
  • Overview of multilevel and structural equation approaches.
  • Simple linear growth model for continuous outcomes.
  • More complex models for continuous outcomes.
  • Mixture modelling including Growth Mixture Modelling (GMM).
  • Methods for incorporating covariates/ outcomes in both LGM's and mixture models.

Please note: Practical sessions of this course will be held in a computer lab, so you will not need to bring a laptop. The course will use Stata and Mplus.

Recommended reading

  • Goldstein H and De Stavola B. Statistical modelling of repeated measurement data. Longitudinal and Lifecourse Studies 2010; 1(2): 170-185.
  • Curran PJ, Hussong AM. The use of latent trajectory models in psychopathology research. Journal of Abnormal Psychology. 2003;112:526–544.



Please note bookings for this course have now closed.

We are currently compiling our 2017/18 course programme. Bookings will open at the beginning of October 2017. Please check back nearer the time for more details.

The course material was comprehensive, well organised and made it easy to keep working on what I learned from the course.

Course feedback, March 2017

Course fees


More information on course fees, fee waivers and reduced prices.

Course venue

School of Social and Community Medicine
Canynge Hall
39 Whatley Road
United Kingdom

Map and directions

Lunch and refreshments

Coffee, tea, fruit and biscuits will be available to all students. A light lunch is provided for all paying participants. Please let us know if you have any dietary requirements.


Information about accommodation.


For further information please email