General Linear Model with applications in ANOVA, Regression Analysis and Factor Analysis


This three day short course provides participants with a firm working knowledge of a wide range of statistical models – many of which are the most commonly used statistical models in the behavioural and social sciences. These models also serve as the fundamental building blocks for advanced statistical models and will be particularly useful for those participants wishing to take more advanced short-courses e.g. the Latent Variable Modelling course.

The course begins by exploring the general linear model and its application in Anova, Ancova, Manova and Mancova with repeated measures models. The short-course will describe simple bivariate regression and correlation and build gradually to the multivariate case, which incorporates a number of predictor variables. In addition to examining regression models with a continuous outcome variable, time will be devoted to data situations in which the outcome variable is either dichotomous or polytomous, i.e. binary and multinomial logistic regression models. Moreover, exploratory factor analysis (EFA) will be covered in some depth, with the focus on its usefulness as a data reduction method: the EFA model primarily involve reducing a large number of observed variables to a lesser number of latent factors, the purpose of which is to explain the structural relationship between the observed variables parsimoniously. The short-course will conclude with an introduction to the Confirmatory Factor Analysis models and its applications using advanced statistical software. The assumptions underpinning the use of all techniques will be considered throughout the short-course, together with identifying some strategies for assessing potential violations.

Each element of the short-course will begin with a lecture to provide participants with a sound conceptual understanding of each statistical model and its application. However, greater emphasis will be placed on practical activity, with participants gaining experience using a hands-on approach to reinforce the learning concepts and to ensure that participants are able to perform the desired analysis and appropriately interpret the output. Days 1 and 2 will be taught primarily using SPSS software with Day 3 using both SPSS and Mplus.

Further information

No prior knowledge is assumed, but some experience of descriptive statistics and hypothesis testing would be helpful.


  • Professor Jamie Murphy

    Jamie Murphy is a Reader in psychology and a member of the Psychology Research Institute at Ulster University.

    He has investigated the expression of psychosis and the co-occurrence of psychological trauma and psychosis for the past 10 years. Challenging traditional disease based conceptualisations of psychosis, Jamie’s research has demonstrated that extreme perceptual, belief and behavioural abnormalities such as hallucinations, delusions and mania often emerge in, and can be understood against, a context of extreme life trauma and adversity.

    Funded by the European Commission’s Horizon 2020 initiative and the UK Economic and Social Research Council, Jamie is published in some of the world’s leading psychiatry and psychology journals, and collaborates with some of the world’s leading authorities in the area. Core branches of his research include: the psychosis continuum; psychotraumatology; childhood sexual abuse and psychosis; social isolation and psychosis; trauma-cannabis interaction and psychosis; and suicidality-psychosis co-occurrence.

    Jamie is also the training coordinator for The Collaborative Network for Training and Excellence in Psychotraumatology (CONTEXT), an EU funded international, interdisciplinary doctoral training programme involving nine European partner organisations spanning the academic, non-governmental, voluntary, and public sectors.

  • Professor Gary Adamson

    Gary Adamson is Professor of psychology at Ulster University and has taught research methods and statistics for over twenty years.

    Professor Adamson has published widely and his research involves the application of latent variable models to issues relating to mental health and wellbeing.

    He has received funding from the Economic and Social Research Council (ESRC) since 2010 to provide courses on Latent Variable Modelling, which he currently delivers in London, Stirling and Ulster.

    He has reviewed for research councils (Medical Research Council, ESRC) and was editor of the Journal of Criminal Psychology and statistical software reviews editor for the British Journal of Mathematical and Statistical Psychology.

  • Dr John Mallett

    John Mallett is a Senior Lecturer at Ulster University and a chartered Psychologist with the British Psychological Society.

    He has acted as reviewer for a range of peer-reviewed publications and as statistical reviewer for the National Institute for Health Research.

    John has been teaching statistics and research methods for over 20 years and has published widely in the areas of psychology, health and social policy. His expertise in advanced statistical analysis is reflected in many of his publications.

    He has obtained research funding from a wide range of organisations and has presented research findings to government departments.

The Vitae Researcher Development Framework

This session maps on to Domain A of the Vitae Framework: Knowledge and intellectual abilities which includes the sub-domain areas of:

  • A1: Knowledge base
  • A2: Cognitive abilities
  • A3: Creativity
The Vitae Researcher Development Framework