Key Facts

  • Module Tutor(s):Dick Wiggins
  • Assessed by: Coursework
  • Credit Value: 15
  • Term: Autumn
  • Access: Open

Data Reduction And Latent Variable Models


Course Code:RMSPAE_12


This two day course combines an introduction to data reduction using principal components analysis and factor analysis to explore the measurement properties of multi-item scales typically used to assess social attitudes and metrics e.g., quality of life, well-being and life satisfaction. The second day introduces students to the principles underlying structural equation modelling starting with measurement models and latent predictors using AMOS software. Students must be familiar with the content of RMSPAE_11 Statistical Analysis.