Modelling Mechanisms of Change - Ulster University 2018

Date:

11/01/2018 - 12/01/2018

Organised by:

Ulster University

Presenter:

Professors Mark Shevlin and Gary Adamson

Level:

Intermediate (some prior knowledge)

Contact:

Professor Mark Shevlin
School of Psychology and
Psychology Research Institute
University of Ulster
Magee campus
Londonderry
BT48 7JL
Northern Ireland
Tel: +44 (0)28 71375619
Email: m.shevlin@ulster.ac.uk

Map:

View in Google Maps  (BT48 7JL)

Venue:

Magee campus
Londonderry
BT48 7JL
Northern Ireland

Description:

 Modelling the Mechanisms of Change – An Introduction to Latent Variable Models.

The School of Psychology at Ulster University is pleased to offer a series of short courses funded by the ESRC under the Advanced Training Initiative. The courses are part of a 3-year programme of training entitled Modelling Mechanisms of Change Using Longitudinal Archived Data. This year’s course will run for 2 days (11th to 12th January 2018) and will provide an introduction to latent variable modelling with an emphasis on longitudinal data analysis. The course is free of charge and available and is available to all social science research students, early career researchers, and academic staff.

The course will be delivered by Professors Mark Shevlin and Gary Adamson from Ulster University.

The courses offered in 2018 will cover the following topics:

  • Overview and applications of latent variable models.
  • Latent growth models.
  • Mixture models.
  • Growth mixture models.
  • Latent transition models.
  • Cross-lagged models with observed and latent variables.
  • Difference score models.
  • Piecewise growth models.

All analyses will be conducted using the SPSS and Mplus software packages. Each day will conclude with a questions and answers session and there will be opportunities for the participants to discuss their own studies with the tutors.

Cost:

Free

Website and registration:

Region:

Northern Ireland

Keywords:

Regression Methods, Longitudinal Data Analysis, Latent Variable Models

Related publications and presentations:

Regression Methods
Longitudinal Data Analysis
Latent Variable Models

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