This two day workshop will use the Mplus programme.
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
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.
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 email@example.com
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.
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 firstname.lastname@example.org.
A 15% discount will be given where the booking is for more than one short course.
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
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.
Price and payment
In this section
- £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)
For further information:
Telephone: (+44) 028 9036 6680