NOTE: Updated R code for use with this volume, along with other resources, is available at: http://privatewww.essex.ac.uk/~ksg/srm_book.html
Spatial Regression Models illustrates the use of spatial analysis in the social sciences. The text includes sections that cover different modeling-related topics: mapping and making projections; doing exploratory spatial data analysis; working with models which have lagged endogenous right-handed side variables; using spatial error correction models; employing conditionally autoregressive models; and dealing with over-time panels exhibiting spatial structures. Each of the modeling-based discussions includes separate delineations of how to proceed when dealing with main variables that are quantitative as well as qualitative. In each section, the authors employ prominent and diverse examples, introducing readers to key literature in the field. The examples are presented along with relevant data and programs written in the R, which illustrate exactly how to undertake the analyses described. The book ends with a chapter that covers techniques for presenting spatial information.
- Geared toward social science readers, unlike other volumes on this topic.
- Illustrates concepts using well-known international, comparative, and national examples of spatial regression analysis.
- Presents each example alongside relevant data and code, which is also available on a Web site maintained by the authors.
Learn more about “The Little Green Book” - QASS Series! Click Here
|Interaction and Social Science|
|Democracy Around the World|
|Introducing Spatial Dependence|
|Maps as Visual Displays of Data|
|Measuring Spatial Association and Correlation|
|Estimating Spatial Models|
|Regression with Spatially Lagged Dependent Variables|
|Estimating the Spatially Lagged y Model|
|Maximum Likelihood Estimates of the Spatially Lagged Y Model of Democracy|
|Equilibrium Effects in the Spatially Lagged y Model|
|Spatial Dependence in Turnout in Italy|
|Using Different Weights Matrices in a Spatially Lagged Dependent Variable Model|
|The Spatially Lagged Dependent Variable Versus OLS with Dummy Variables|
|The Spatial Error Model|
|Maximum Likelihood Estimation of the Spatial Errors Model|
|Example: Democracy and Development|
|Spatially Lagged y Versus Spatial Errors|
|Assessing Spatial Error in Dyadic Trade Flows|
|Inference and Model Evaluation|
|Appendix: Software Options|