Spatial Analysis for the Social Sciences

David Darmofal is an Associate Professor of Political Science at the University of South Carolina. His research focuses on spatial analysis and political geography and has appeared in a variety of journals including the American Journal of Political Science, the Journal of Politics, and Political Geography. He has received best article awards from the Journal of Politics and Political Research Quarterly. He teaches regularly in the ICPSR Summer Program in Quantitative Methods of Social Research.

• Part I. General Topics: 1. The social sciences and spatial analysis; 2. Defining neighbors via a spatial weights matrix; 3. Spatial autocorrelation and statistical inference; 4. Diagnosing spatial dependence; 5. Diagnosing spatial dependence in the presence of covariates; 6. Spatial lag and spatial error models; 7. Spatial heterogeneity; Part II. Advanced Topics: 8. Time-series-cross-section (TSCS) and panel data models; 9. Advanced spatial models; 10. Conclusion; Part III. Appendices on Implementing Spatial Analyses: 11. Getting data ready for a spatial analysis; 12. Spatial software; 13. Web resources for spatial analysis; 14. Glossary.

'Do you collect all your data from just one place? Would the geography of what your research covers look like a single dot on a map? If so, then don't read David Darmofal's interesting and accessible book on spatial statistics. And definitely skip the practical discussion of software that shows you how to improve your statistical analyses to account for geographic dependencies.' Gary King, Albert J. Weatherhead III University Professor, and Director, Institute for Quantitative Social Science, Harvard University, Massachusetts