Spatial Regression Models for the Social Sciences

Spatial Regression Models for the Social Sciences

Author: Guangqing Chi

Publisher: SAGE Publications

Published: 2019-03-06

Total Pages: 229

ISBN-13: 1544302053

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Spatial Regression Models for the Social Sciences shows researchers and students how to work with spatial data without the need for advanced mathematical statistics. Focusing on the methods that are commonly used by social scientists, Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it by connecting it to social science research topics. Throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us.


Book Synopsis Spatial Regression Models for the Social Sciences by : Guangqing Chi

Download or read book Spatial Regression Models for the Social Sciences written by Guangqing Chi and published by SAGE Publications. This book was released on 2019-03-06 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Regression Models for the Social Sciences shows researchers and students how to work with spatial data without the need for advanced mathematical statistics. Focusing on the methods that are commonly used by social scientists, Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it by connecting it to social science research topics. Throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us.


Spatial Analysis for the Social Sciences

Spatial Analysis for the Social Sciences

Author: David Darmofal

Publisher: Cambridge University Press

Published: 2015-11-12

Total Pages: 263

ISBN-13: 0521888263

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This book shows how to model the spatial interactions between actors that are at the heart of the social sciences.


Book Synopsis Spatial Analysis for the Social Sciences by : David Darmofal

Download or read book Spatial Analysis for the Social Sciences written by David Darmofal and published by Cambridge University Press. This book was released on 2015-11-12 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how to model the spatial interactions between actors that are at the heart of the social sciences.


Spatial Regression Models

Spatial Regression Models

Author: Michael D. Ward

Publisher: SAGE Publications

Published: 2018-04-10

Total Pages: 129

ISBN-13: 1544328842

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Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers 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. Using social sciences examples based on real data, Michael D. Ward and Kristian Skrede Gleditsch illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.


Book Synopsis Spatial Regression Models by : Michael D. Ward

Download or read book Spatial Regression Models written by Michael D. Ward and published by SAGE Publications. This book was released on 2018-04-10 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The text covers 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. Using social sciences examples based on real data, Michael D. Ward and Kristian Skrede Gleditsch illustrate the concepts discussed, and show how to obtain and interpret relevant results. The examples are presented along with the relevant code to replicate all the analysis using the R package for statistical computing. Users can download both the data and computer code to work through all the examples found in the text. New to the Second Edition is a chapter on mapping as data exploration and its role in the research process, updates to all chapters based on substantive and methodological work, as well as software updates, and information on estimation of time-series, cross-sectional spatial models.


GIS and Spatial Analysis for the Social Sciences

GIS and Spatial Analysis for the Social Sciences

Author: Robert Nash Parker

Publisher: Routledge

Published: 2009-09-10

Total Pages: 254

ISBN-13: 1135857598

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This is the first book to provide sociologists, criminologists, political scientists, and other social scientists with the methodological logic and techniques for doing spatial analysis in their chosen fields of inquiry. The book contains a wealth of examples as to why these techniques are worth doing, over and above conventional statistical techniques using SPSS or other statistical packages. GIS is a methodological and conceptual approach that allows for the linking together of spatial data, or data that is based on a physical space, with non-spatial data, which can be thought of as any data that contains no direct reference to physical locations.


Book Synopsis GIS and Spatial Analysis for the Social Sciences by : Robert Nash Parker

Download or read book GIS and Spatial Analysis for the Social Sciences written by Robert Nash Parker and published by Routledge. This book was released on 2009-09-10 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to provide sociologists, criminologists, political scientists, and other social scientists with the methodological logic and techniques for doing spatial analysis in their chosen fields of inquiry. The book contains a wealth of examples as to why these techniques are worth doing, over and above conventional statistical techniques using SPSS or other statistical packages. GIS is a methodological and conceptual approach that allows for the linking together of spatial data, or data that is based on a physical space, with non-spatial data, which can be thought of as any data that contains no direct reference to physical locations.


Spatial Regression Models

Spatial Regression Models

Author: Michael Don Ward

Publisher: SAGE

Published: 2008-02-29

Total Pages: 113

ISBN-13: 1412954150

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Assuming no prior knowledge this book is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on a Web site maintained by the authors.


Book Synopsis Spatial Regression Models by : Michael Don Ward

Download or read book Spatial Regression Models written by Michael Don Ward and published by SAGE. This book was released on 2008-02-29 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assuming no prior knowledge this book is geared toward social science readers, unlike other volumes on this topic. The text illustrates concepts using well known international, comparative, and national examples of spatial regression analysis. Each example is presented alongside relevant data and code, which is also available on a Web site maintained by the authors.


Spatial Regression Analysis Using Eigenvector Spatial Filtering

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Author: Daniel Griffith

Publisher: Academic Press

Published: 2019-09-14

Total Pages: 286

ISBN-13: 0128156929

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Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics


Book Synopsis Spatial Regression Analysis Using Eigenvector Spatial Filtering by : Daniel Griffith

Download or read book Spatial Regression Analysis Using Eigenvector Spatial Filtering written by Daniel Griffith and published by Academic Press. This book was released on 2019-09-14 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre. Reviews the uses of ESF across linear regression, generalized linear regression, spatial autocorrelation measurement, and spatially varying coefficient models Includes computer code and template datasets for further modeling Provides comprehensive coverage of related concepts in spatial data analysis and spatial statistics


Spatial Data Analysis in the Social and Environmental Sciences

Spatial Data Analysis in the Social and Environmental Sciences

Author: Robert P. Haining

Publisher: Cambridge University Press

Published: 1993-08-26

Total Pages: 436

ISBN-13: 9780521448666

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Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data description, map interpolation, and exploratory and explanatory analyses. The book also examines spatial referencing, and methods for detecting problems, assessing their seriousness and taking appropriate action are discussed. This is an important text for any discipline requiring a broad overview of current theoretical and applied work for the analysis of spatial data sets. It will be of particular use to research workers and final year undergraduates in the fields of geography, environmental sciences and social sciences.


Book Synopsis Spatial Data Analysis in the Social and Environmental Sciences by : Robert P. Haining

Download or read book Spatial Data Analysis in the Social and Environmental Sciences written by Robert P. Haining and published by Cambridge University Press. This book was released on 1993-08-26 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data description, map interpolation, and exploratory and explanatory analyses. The book also examines spatial referencing, and methods for detecting problems, assessing their seriousness and taking appropriate action are discussed. This is an important text for any discipline requiring a broad overview of current theoretical and applied work for the analysis of spatial data sets. It will be of particular use to research workers and final year undergraduates in the fields of geography, environmental sciences and social sciences.


Spatial Econometrics: Methods and Models

Spatial Econometrics: Methods and Models

Author: L. Anselin

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 295

ISBN-13: 9401577994

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Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.


Book Synopsis Spatial Econometrics: Methods and Models by : L. Anselin

Download or read book Spatial Econometrics: Methods and Models written by L. Anselin and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.


New Directions in Spatial Econometrics

New Directions in Spatial Econometrics

Author: Luc Anselin

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 432

ISBN-13: 3642798772

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The promising new directions for research and applications described here include alternative model specifications, estimators and tests for regression models and new perspectives on dealing with spatial effects in models with limited dependent variables and space-time data.


Book Synopsis New Directions in Spatial Econometrics by : Luc Anselin

Download or read book New Directions in Spatial Econometrics written by Luc Anselin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The promising new directions for research and applications described here include alternative model specifications, estimators and tests for regression models and new perspectives on dealing with spatial effects in models with limited dependent variables and space-time data.


Introduction to Spatial Econometrics

Introduction to Spatial Econometrics

Author: James LeSage

Publisher: CRC Press

Published: 2009-01-20

Total Pages: 362

ISBN-13: 1420064258

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Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat


Book Synopsis Introduction to Spatial Econometrics by : James LeSage

Download or read book Introduction to Spatial Econometrics written by James LeSage and published by CRC Press. This book was released on 2009-01-20 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat