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Structural Equation Modelling with Stata - 9 May 2022 to 20 May 2022

Please note that this event has passed.


Course overview: This module is an introduction into path analysis and structural equation modelling using the Stata software. Themodule features an introduction to the logic of SEM, including assumptions, modelspecification, identification and estimation. Models for continuous and discrete response variables and continuousand discrete latent variables will be covered. Growth, autoregressive, MIMIC, andinstrumental variable models will be included.

Requirements:

This workshop will assume that participants have a good knowledge of:

  • Basic regression and statistical modelling
  • Writing code to run statistical models/syntax based statistical software, and familiarity with the Statasoftware specifically (such as can be obtained from the BHI Introduction to Stata course). Participantswill need to provide their own laptop computer with Stata installed.

Learning outcomes:

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 models 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 and to interact effectively in a group

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