Applied Psychometrics

Tutorial materials: 2 and 3-day short courses

  1. Introduction to Mplus: latent variables, traits and classes.
    Introduction to the Mplus modelling environment covering Exploratory Factor Analysis (EFA) with different rotations, Confirmatory Factor Analysis (CFA), regression and path analysis, multiple-group analysis and Latent Class Analysis (LCA). Read more...
  2. Confirmatory Factor Analysis in Mplus
    Introduction to the analysis of psychometric data emerging from ability tests and personality questionnaires, covering best practice for performing Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA)with scale and item-level test data in realistic conditions. Read more...
  3. Measurement invariance and Differential Item Functioning (DIF)
    Introduction to concepts of measurement invariance, covering the cases of categorical item response data (DIF studies) and continuous data (factorial invariance studies). Software packages used for this course are DIFAS, R and Mplus. Read more...
  4. Introduction to Longitudinal Modelling
    Introduction to most popular longitudinal designs and models, and issues of measurement invariance across time. Models include autoregressive, latent dynamic models, and latent growth models, and the growth mixture modelling approach to exploring typical development trajectories in longitudinal data. All modelling is carried out using Mplus. Read more...
  5. Structural Equation Modelling (SEM)
    Introduction to Structural Equation Modelling using Mplus. Simple and advanced methods including measurement models, path analysis, and full structural models with continuous and categorical variables. Read more...
  6. Summer schools

  7. Introduction to Item Response Theory (IRT)
    Introduction to the latent trait approach to modelling test items. Simple IRT models for binary and ordinal test items and their application to measurement, including studies of measurement invariance and bias. Software packages used for this course are R, Mplus, and DIFAS. Read more...
  8. Psychometric modelling of Patient-Reported Outcome Measures (PROMs)
    Introduction to advanced psychometric modelling of self-reported questionnaires, specifically concentrating on Patient-Reported Outcome Measures (PROMs). Classical and modern views and conceptions of reliability, validity and sensitivity of clinical measures using multiple approaches and methods, including advanced multidimensional modelling with Item Response Theory (IRT). Software packages used for this course are R, Mplus, IRTscore and DIFAS. Read more...