This course links statistical modelling concepts and data analysis to establish a firm knowledge of statistical models to analyse longitudinal data.
The course seeks to develop participants' knowledge and understanding of methods for analysing longitudinal data within a latent variable framework. Latent growth models, mixture models and models involving mediation and moderation will be described, together with combinations thereof. Participants will be introduced to the concepts, terms and approaches underlying these models and will gain experience implementing and estimating the models using appropriate statistical software.
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
A researcher’s ability to measure and describe how individuals change over time is central to understanding much psychological and social phenomena. Throughout the lifespan, individuals may follow similar patterns of change as they develop or they may change inresponse to various positive or negative life experiences. Latent Growth Models are an important class of statistical models that facilitates the assessment of change over time.Moreover, the curious researcher often wishes to extend their understanding by identifying and quantifying those life events or personal characteristics that may influence or predict individual change. They may also wish to assess how certain variables can be mediators or moderators of individual change, or indeed, researchers may wish to explore the presence of unobserved groups of individuals through mixture modelling. These are important and common research questions, all of which can be readily accommodated and addressed in the latent variable modelling context.
The course will introduce and develop participants’ knowledge of a range of statistical models for analysing longitudinal data, together with applying statistical models for assessing moderation and mediation effects and methods for unpacking unobserved heterogeneity.The course employs an integrated framework linking statistical modelling concepts and data analysis using statistical software to establish a firm knowledge of statistical models useful for analysing longitudinal data.
Linked programmesPgCertPD Postgraduate Certificate of Professional Development, PgCert Quantitative Methods for the Behavioural and Social Sciences
100% coursework - (a) Report - written practical report in a standard format expected in social science research, with the focus on hypothesis construction and testing and the production and interpretation of statistical output (60%) and (b) Online Class Test (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