This course provides participants with the knowledge and skills to specify and test a range of statistical models within a LVM framework.
This course introduces participants to the principles of latent variable modelling (LVM) and how such statistical models can be specified and tested. LVM is now the preferred method of statistical analyses in all social sciences due to its power and flexibility. This course will cover the theoretical and statistical basis of LVM, and provide the participants with the skills to specify, estimate and interpret such models.
This course can be taken individually or combined over a period of time towards a Postgraduate Certificate of Professional Development https://www.ulster.ac.uk/courses/201819/postgraduate-certificate-of-professional-development-16046
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About this course
In this section
This course provides participants with the knowledge and skills to specify and test a range of statistical models within a LVM framework. In addition, participants will develop an understanding of the interpretation of different model parameters and overall indices of model-fit.
Latent variable modelling (LVM) is a flexible statistical model that allows researchers to specify, estimate, and interpret complex socio-behavioural models. The power of LVM is derived from its ability to (1) specify statistical models that include latent variables, (2) control for the deleterious effects of measurement error, and (3) provide objective indicators of model fit. LVM can replace many common types of statistical analysis in psychology, such as analysis of (co)variance (comprising multivariate and repeated measures), bivariate/multiple and multivariate regression and correlation, and factor analysis. LVM provides a much more flexible and statistically robust framework with which to test complex hypotheses. LVM can readily accommodate models that include direct and indirect effects, interactions, parameters that are constrained to be equal or be a function of other parameters, reciprocal relations and mean differences between groups within one specified model. LVM is now the preferred method of analysis in many social science disciplines and is increasingly becoming the industry-standard for reporting statistical analyses in peer reviewed journals.
Linked programmesPgCertPD Postgraduate Certificate of Professional Development, PgCert Quantitative Methods for the Behavioural and Social Sciences
100% coursework - (a) Practical Report based on analysis of a secondary data resource (60%) and (b) Set exercise critiquing an online video applying statistical techniques to quantitative data (40%).
This course requires attendance for three full days (9am - 5pm) during the period from 20 August to 31 August 2018 (dates to be confirmed).
Degree in the behavourial or social sciences (e.g. psychology, geography, political science, health econmics, sociology or equivalent).
English Language Requirements
Applicants whose first language is not English must meet the minimum English entrance requirements of the University and will need to provide recent evidence of this (certified within the last two years).
Most of our courses require a minimum English level of IELTS 6.0 or equivalent, with no band score under 5.5. Trinity ISE: Pass at level III also meets this requirement.
Please see details of the English language qualifications and certificates we can accept - https://www.ulster.ac.uk/__data/assets/pdf_file/0005/177404/Other-english-language-tests-and-qualifications-2017.pdf
International applicants will also require a short-term study visa. Further information is available at https://www.ulster.ac.uk/international/visa-immigration
- 20 August 2018
Fees and funding
In this section
- Northern Ireland & EU:
- England, Scotland & Wales:
Information about how to pay for a course including different payment options is available at
Scholarships, awards and prizes
Fee waivers may be available to those who meet the eligibility criteria. More information is available from FlexEd@ulster.ac.uk