This fourth module of the Spatial Regression Modeling workshop concerns Spatial Heterogeneity and Spatial Regression Diagnostics and Model Strategies.There are a number of readings that will help you prepare for and better understand this module and a lecture about the topic.
- Wheeler, D. and M. Tiefelsdorf. 2005. Multicollinearity and Correlation among Local Regression Coefficients in Geographically Weighted Regression. Journal of Geographical Systems 7: 161–187. [GWR has its critics]
- O’Loughlin, J., C. Flint, and L. Anselin. 1994. The Geography of the Nazi Vote: Context, Confession, and Class in the Reichstag Election of 1930. Annals of the Association of American Geographers 84(3): 351–380. [Excellent example of regime analysis]
- Cahill, M. and G. Mulligan. 2007. Using Geographically Weighted Regression to Explore Local Crime Patterns. Social Science Computer Review 25(2): 174–193. [One of many empirical applications of GWR]
- Grose, D., C. Brunsdon, and R. Harris. No date. Introduction to Geographically Weighted Regression (GWR) and to Grid Enabled GWR. [How to for R]
- Harris, R., A. Singleton, D. Grose, C. Brunsdon, and P. Longley. 2010. Grid-enabling Geographically Weighted Regression: A Case Study of Participation in Higher Education in England. Transactions in GIS 14(1): 43–61. [GWR for particularly large data sets]
- Anselin, L. 2007. Discrete Spatial Heterogeneity, and Continuous Spatial Heterogeneity. In Spatial Regression Analysis in R: A workbook. Pp. 102–115 and 116–130
Spatial Heterogeneity and Spatial Regression Diagnostics and Model Strategies are two presentations from the Spatial Regression Modeling workshop. These presentations were given by Drs. Paul Voss and Katherine Curtis on June 23, 2011.
We have broken this lecture into three parts, which can be accessed by the page links below. Each lecture is presented through video recordings, audio recordings, lecture slides and notes on the lectures.