Spatial Regression Models, 2nd ed. illustrates the use of spatial analysis in the social sciences within a regression framework. The book is accessible to readers without prior background in spatial analysis. Spatial Regression Models, 2nd ed.
includes sections that cover different modeling-related topics for continuous dependent variables, including: mapping data on spatial units, exploratory spatial data analysis, working with regression models that have spatially dependent regressors, and estimating regression models with spatially correlated error structures. In each section, the authors employ examples from the social sciences based on real data to illustrate the concepts discussed, how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the freely available R package for statistical computing. Users can download both the data and computer code and work through all the examples found in the text. The final section examines various extensions from the regression models discussed, and provides pointers to additional spatial techniques. New to the Second Edition is a new chapter on mapping as data exploration and its role in the research process, and updates to all chapters based on substantive and methodological work, as well as software updates, since the previous edition.
"Ward and Gleditsch provide a valuable and highly accessible introduction to spatial analysis, including data and code for in-text examples and other course materials in an online repository. This is an excellent supplement for any introduction to spatial analysis!"
-- Matthew Ingram
"This `Little Green Book' by Ward and Gleditsch introduces the fundamental concepts of spatial regression models. It is good for both introductory and intermediate level of students who like to implement spatial regression models into their research."
-- Changjoo Kim
"This text provides a solid introduction to spatial thinking and spatial regression modeling for social scientists that transcends disciplinary boundaries, and will provide a valuable resource for students and professionals alike who are new to this material."
-- Corey Sparks
"Spatial statistics is becoming increasingly important to all fields of social science. This book does a good job of providing a brief and essential introduction to core ideas in spatial statistics."
-- Juan Sandoval
Chapter 1: Why Space in the Social Sciences?
Chapter 2: Maps as Displays of Information
Chapter 3: Interdependency Among Observations
Chapter 4: Spatially Lagged Dependent Variables
Chapter 5: Spatial Error Model
Chapter 6: Extensions
Series: Quantitative Applications in the Social Sciences
Tertiary; University or College
Number Of Pages: 128
Published: 24th April 2018
Publisher: SAGE Publications Inc
Country of Publication: US
Dimensions (cm): 21.0 x 14.0
Weight (kg): 0.15
Edition Number: 2
Edition Type: Revised