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Courses offered

Multilevel and Longitudinal Modelling

Academic Lead: Prof Richard Emsley

Date: 18th February 2019 – 22nd February 2019

Venue: Seminar 1 and 2, Main Building, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London. View Map.


  • External Early bird: £675 (till 15/10/18, price thereafter £750)
  • KCL Staff Early bird: £506.25 (till 15/10/18, price thereafter £562.5)
  • KCL Student Early bird: £337.5 (till 15/10/18, price thereafter £475)
  • Other Student Early bird: £506.25 (till 15/10/18, price thereafter £562.5)
  • Kings Health Partner Early bird: £506.25 (till 15/10/18, price thereafter £562.5)

Last booking: 7th February 2019

BOOKING: Booking for this course has now closed. 



As health care data becomes more complex and multimodal, the structure of the data becomes increasingly complicated. There could be an increasing number of repeated measurements on the same individuals over time, longer duration of follow-up for time-to-event outcomes or nested hierarchies leading to non-independence of individuals. The use of simpler statistical approaches to analyse these data is invalid because the key assumptions of the those approaches do not hold. In this module, we introduce the concept of multilevel and longitudinal modelling, including time-to-event or survival analysis. The aim is for the student to understand the challenges of longitudinal and

clustered data, and the concept and implementation of multilevel models. Students will also become familiar with the most common models for time-to-event data (inc. Cox proportional hazard models, additive hazard models), and finally link all these concepts together through joint modelling of survival and longitudinal data. Students will discover Stata commands that can fit all of these models and become familiar with the resulting Stata output, whilst applying them to real data structures.


This workshop will assume that participants have a good knowledge of basic regression and statistical modelling (as can be gained in the BHI Introduction to Statistical Modelling course running in January) any syntax based statistical software, such as STATA (such as can be obtained from the BHI Introduction to Programming course running in October or the Introduction to STATA course running in January).

*** Participants will need to bring their own laptop computer with STATA installed. ***


Subject specific: Knowledge, Understanding and Skills

  • To properly interpret a multilevel model, and its parameter estimates
  • To specify multilevel models, appropriate to an example study data setting
  • To implement multilevel models in Stata and be able to interpret the output
  • To achieve the above for continuous and binary responses
  • To properly interpret a time-to-event model, and its parameter estimates
  • To specify time-to-event models appropriate to an example study data setting
  • To implement time-to-event models in Stata and be able to interpret the output
  • To properly interpret a joint model and its parameters estimates
  • To implement joint models in Stata and be able to interpret the output
  • To read, understand, critique and discuss an application in the research literature
  • To make use of face-to-face learning to apply multilevel modelling or survival analysis to a typical example dataset to address a particular scientific problem

General: Knowledge, Understanding and Skills 

On successful completion of this module the student should be able to:

  • Justify and critique the use of statistical methods for real life applications.
  • Show confidence in the use of STATA to implement statistical models for real life application.
  • Interact effectively in a group through discussion forums
  • Identify key features of data, specify analysis goals and objectives, and operationalize into an appropriate statistical model
  • Develop and rehearse ability to communicate analysis findings clearly.


Please note the following:

If you would like to pay by internal transfer, please contact 

Your place will not be confirmed until payment has been made.

Failure cancel without sufficient notice will forfeit your course fee and access to future courses.

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