Spatial Models of Parliamentary Voting

by

Keith T. Poole

Cambridge University Press, 2005


Chapter 5

The R program for Figure 5.1 is a general program that reads a roll call matrix, double-centers it, and then does a two-dimensional plot. It is set up to read any of my roll call data files -- SEN01KH.ORD/HOU01KH.ORD to SEN108KH.ORD/HOU108KH.ORD -- by changing just a few statements in the code. My thanks to Jeff Lewis for writing the read.ord routine!

Figure 5.1: R Program To Create Torgerson Coordinates for the 90th U.S. Senate
Figure 5.2: R Program To Create Plot Common Space Coordinates for the 90th U.S. Senate
The R program for Figure 5.4 is the same as for Figure 5.1 only it opens a second graphics window to do the plot of the normalized eigenvalues. It is set up to read any of my roll call data files -- SEN01KH.ORD/HOU01KH.ORD to SEN108KH.ORD/HOU108KH.ORD -- by changing just a few statements in the code. Again, my thanks to Jeff Lewis for writing the read.ord routine!

Figure 5.4: R Program To Plot Normalized Eigenvalues for the 90th U.S. Senate
This program is the same as Figure 5.4 except for the labeling. Note that the two-dimensional Torgerson Coordinates are very poor because the 108th Senate was almost unidimensional.

Figure 5.5: R Program To Plot Normalized Eigenvalues for the 108th U.S. Senate
Figure 5.6: R Program To Plot Late Term Abortion Vote in the 108th U.S. Senate
This program is the same as Figure 5.4 except that the read function has been customized for the format of the United Nations data. Note that the Torgerson Coordinates are very similar to the OC Scaling Coordinates in Figure 5.8.

Figure 5.7: R Program To Plot Normalized Eigenvalues for Sessions 1-3 of the United Nations
Figure 5.8: R Program To Plot Two Dimensional OC Coordinates for Countries in Sessions 1-3 of the United Nations
Figure 5.9: R Program To Plot Two Dimensional OC Coordinates for French National Assembly 1946-1958
Figure 5.10: R Program To Illustrate How to Interpret the Dimensions of the 106th House
Figure 5.11: R Program To Illustrate the Sag Problem

Book Chapters

Spatial Models of Parliamentary Voting
Chapter 1: Introduction
Chapter 2: The Geometry of Parliamentary Roll Call Voting
Chapter 3: The Optimal Classification Method
Chapter 4: Probabilistic Spatial Models of Parliamentary Voting
Chapter 5: Practical Issues in Computing Spatial Models of Parliamentary Voting
Chapter 6: Conducting Natural Experiments with Roll Calls
Chapter 7: Conclusion

Homework Problems



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