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Overview

This two day workshop will use the Mplus programme.

Summary

The analysis of change is central to much psy­chological and social research. Latent Growth Models (LGM) are an important class of models for the assessment of change. In essence these describe individuals’ behaviour in terms of an initial starting point (intercept) and their subsequent devel­opmental trajectories (slope).

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About this course

In this section

About

Synopsis of the course


The analysis of change is central to much psy­chological and social research. Latent Growth Models (LGM) are an important class of models for the assessment of change. In essence these describe individuals’ behaviour in terms of an initial starting point (intercept) and their subsequent devel­opmental trajectories (slope). The technique also allows for the introduction of predictors (covariates) of change. These predictors can be both time-invariant and time-varying and the model can be extended to incorporate other ad­vantages of latent variable framework, e.g., the ability to handle missing data, to introduce both direct and indirect effects and correction for measurement error.

In the context of longitudinal data, latent variable modelling facilitates robust estimation of direct and indirect effects, together with controlling for, and assessing the impact of, moderating and mediating variables. This session will introduce some of the recent developments in the area. Furthermore, applications of the Cross-lagged panel model will be explored and extended to include mixture distributions.

Growth mixture models (GMMs) will be introduced. These models enable the researcher to explore longitudinal data for the presence of unobserved or latent subgroups. In GMMs the assumption of a single homogenous population with a single growth trajectory is relaxed. Instead, a latent categorical variable is introduced with the intention of capturing latent subpopulations in the longitudinal data. These subpopulations are not directly observed, but are inferred from the patterns of responses in the data. In sum, the GMM facilitates the exploration of longitudinal data for unobserved subgroups and estimates latent growth parameters for each of the subgroups.

Further information

This workshop will use the Mplus programme. It is expected that participants will have some knowledge and understanding of Structural Equation Modelling. This two day course will be held on Coleraine Campus, Ulster University.

If you have any queries about this course, please contact the course leader Dr James Houston at je.houston@ulster.ac.uk

Cancellation Policy
Cancellations made prior to Monday 7th August 2017: full refund less an administrative charge of £50.00.
Cancellations made between Monday 7th August and Monday 14th August: refund of fifty percent.
Cancellations made after Monday 14th August: no refund to be made.

Accommodation

Students can find information relating to accommodation at https://www.ulster.ac.uk/accommodation/forms-and-documents/summer-non-students.

If accommodation is unavailable please contact James Houston at je.houston@ulster.ac.uk.


A 15% discount will be given where the booking is for more than one short course.

Attendance

This two day course will be held in Coleraine Campus, Cromore Road, Coleraine, BT52 1SA. (Room location tbc).

Date: Thursday 14th & Friday 15th September 2017
Time: 9.30 am - 4.30 pm

Entry requirements

It is expected that participants will have some knowledge and understanding of Structural Equation Modelling. This two day course will be held on Coleraine Campus, Ulster University.

Start dates

Apply

All applications and payments for short course programmes must be made online at http://store.ulster.ac.uk/

Start dates

Price and payment

In this section

Price

£300.00

Payment information

  • £300 (Full Fee)
  • £200 (Concessionary Fee for Unwaged/Students/Charitable Sector Workers - evidence will be required)
  • £255(Full Fee booking with more than one course)
  • £170 (Concessionary Charge with more than one course)

Contact

For further information:

Email: FlexEd@ulster.ac.uk

Telephone: (+44) 028 9036 6680