This module provides the theoretical foundations and applied advice for models for multivariate data - models where there are multiple dependent variables. There are two broad classes of models covered here.
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Multivariate statistical routines - those that model the structure in observed dependent variables with observed independent variables
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Models of the structure in observed dependent variables with unobserved (i.e., latent) independent variables.
The outline for the course is below.
1 Summated Rating Model, Principal Components, Factor Analysis
2 Spatial Theories, Analyzing Issue Scales
3 Multidimensional Scaling (similarities data)
- Slides pdf
- Code r
- In-class Exercises Code r
- Data zip
- Comparison of Scaling Outcomes pdf
- BSMDS Source Code tar.gz
- To use the bsmds package, you’ll have to install it from source. This means - download the package, reset R’s working directory to the location of the file you downloaded, then do:
install.packages("bsmds_0.1-2.tar.gz", type="source", repos=NULL)
4 Unfolding of Ratings Scale Data
5 Parametric Methods for Binary Data
6 Non-parametric Methods for Binary Data
- Slides pdf
- Code r
- In-class Exercises Code r
- WVS Data .rda
- European Court for Human Rights Data .rda
- 2004 Feeling Thermometers Data .rda