Data Reduction And Latent Variable Models
- Level
Data Reduction And Latent Variable Models
Starting dates and places
This product does not have fixed starting dates and/or places.
Description
Course Code: RMSPAE_12
Masters Level Module
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.
Frequently asked questions
There are no frequently asked questions yet. If you have any more questions or need help, contact our customer service.
Course Code: RMSPAE_12
Masters Level Module
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.
Share your review
Do you have experience with this course? Submit your review and help other people make the right choice. As a thank you for your effort we will donate £1.- to Stichting Edukans.There are no frequently asked questions yet. If you have any more questions or need help, contact our customer service.