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Structural Equation Modelling with STATA

Academic Leads: Prof Andrew Pickles and Prof Richard Emsley

Date: 1st April – 5th April 2019

Time: 09:00-17:30

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


  • External Early bird: £855 (till 18/10/18, price thereafter £950)
  • KCL Staff Early bird: £641.25 (till 18/10/18, price thereafter £712.5)
  • KCL Student Early bird: £427.5 (till 18/10/18, price thereafter £475)
  • Other student Early bird: £641.25 (till 18/10/18, price thereafter £712.5)

Last booking: 21st March 2019

BOOKING: Booking for this course has now closed.



This 5-day course is aimed at post-graduate research students, researchers and professionals.  The course is an introduction into path analysis and structural equation modelling using the STATA software. The course features an introduction to the logic of SEM, including assumptions, model specification, identification and estimation. Models for continuous and discrete response variables and continuous and discrete latent variables will be covered.  Growth, autoregressive, MIMIC, and instrumental variable models will be included.


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 BHI 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

On successful completion of this course the student should be able to

  • To properly interpret a path diagram, and its parameter estimates.
  • To gain insight into the impact of measurement error on estimates of structural parameters.
  • To specify a structural equation model appropriate to an example study data setting.
  • To specify simple structural equation model using graphical and script-based interfaces.
  • To implement a structural equation model in Stata and be able to interpret the output.
  • To be able to access and interpret postestimation statistics, tests and functions of parameters.
  • To achieve the above for continuous and discrete response and latent variables.
  • To make use of face-to-face learning to apply SEM 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

  • Identify key features of data, client goals and objectives, and operationalize into an appropriate model Develop and rehearse ability
  • To communicate analysis findings clearly and accurately
  • Interact in a group.


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

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