Spatial Regression Models For The Social Sciences

Author : Guangqing Chi,Jun Zhu
Publisher : SAGE Publications
Page : 273 pages
File Size : 49,5 Mb
Release : 2019-03-06
Category : Social Science
ISBN : 9781544302089

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Spatial Regression Models for the Social Sciences by Guangqing Chi,Jun Zhu Pdf

Space and geography are important aspects of social science research in fields such as criminology, sociology, political science, and public health. Many social scientists are interested in the spatial clustering of various behaviors and events. There has been a rapid development of interest in regression methods for analyzing spatial data over recent years, but little available on the topic that is aimed at graduate students and advanced undergraduate classes in the social sciences (most texts are for the natural sciences, or regional science, or economics, and require a good understanding of advanced statistics and probability theory). Spatial Regression Models for the Social Sciences fills the gap, and focuses on the methods that are commonly used by social scientists. Each spatial regression method is introduced in the same way. 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. They try to avoid mathematical formulas and symbols as much as possible. Secondly, throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us. Spatial Regression Models for the Social Sciences provides comprehensive coverage of spatial regression methods for social scientists and introduces the methods in an easy-to-follow manner.

Author : Guangqing Chi,Jun Zhu (Professor of statistics)
Publisher : Unknown
Page : 272 pages
File Size : 53,9 Mb
Release : 2019
Category : Social sciences
ISBN : 1071849077

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Spatial Regression Models for the Social Sciences by Guangqing Chi,Jun Zhu (Professor of statistics) Pdf

Author : David Darmofal
Publisher : Cambridge University Press
Page : 263 pages
File Size : 43,5 Mb
Release : 2015-11-12
Category : Political Science
ISBN : 9780521888264

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Spatial Analysis for the Social Sciences by David Darmofal Pdf

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

Author : Michael Don Ward,Kristian Gleditsch (jurist)
Publisher : SAGE
Page : 113 pages
File Size : 41,8 Mb
Release : 2008-02-29
Category : Mathematics
ISBN : 9781412954150

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Spatial Regression Models by Michael Don Ward,Kristian Gleditsch (jurist) Pdf

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.

Author : Robert Nash Parker,Emily K. Asencio
Publisher : Routledge
Page : 254 pages
File Size : 48,6 Mb
Release : 2009-09-10
Category : Political Science
ISBN : 9781135857592

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GIS and Spatial Analysis for the Social Sciences by Robert Nash Parker,Emily K. Asencio Pdf

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.

Author : Michael D. Ward,Kristian Skrede Gleditsch
Publisher : SAGE Publications
Page : 129 pages
File Size : 54,7 Mb
Release : 2018-04-10
Category : Social Science
ISBN : 9781544328843

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Spatial Regression Models by Michael D. Ward,Kristian Skrede Gleditsch Pdf

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.

Author : Guangqing Chi,Jun Zhu
Publisher : SAGE Publications
Page : 229 pages
File Size : 51,6 Mb
Release : 2019-03-06
Category : Social Science
ISBN : 9781544302058

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Spatial Regression Models for the Social Sciences by Guangqing Chi,Jun Zhu Pdf

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.

Author : Daniel Griffith,Yongwan Chun,Bin Li
Publisher : Academic Press
Page : 286 pages
File Size : 52,6 Mb
Release : 2019-09-14
Category : Business & Economics
ISBN : 9780128156926

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Spatial Regression Analysis Using Eigenvector Spatial Filtering by Daniel Griffith,Yongwan Chun,Bin Li Pdf

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

Author : Robert P. Haining,Robert Haining
Publisher : Cambridge University Press
Page : 436 pages
File Size : 45,6 Mb
Release : 1993-08-26
Category : Mathematics
ISBN : 0521448662

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Spatial Data Analysis in the Social and Environmental Sciences by Robert P. Haining,Robert Haining Pdf

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.

Author : James LeSage,Robert Kelley Pace
Publisher : CRC Press
Page : 362 pages
File Size : 54,5 Mb
Release : 2009-01-20
Category : Business & Economics
ISBN : 9781420064254

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Introduction to Spatial Econometrics by James LeSage,Robert Kelley Pace Pdf

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

Author : Manfred M. Fischer,Jinfeng Wang
Publisher : Springer Science & Business Media
Page : 80 pages
File Size : 52,7 Mb
Release : 2011-08-05
Category : Business & Economics
ISBN : 3642217206

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Spatial Data Analysis by Manfred M. Fischer,Jinfeng Wang Pdf

The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.

Author : Luc Anselin,Raymond Florax
Publisher : Springer Science & Business Media
Page : 432 pages
File Size : 53,9 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642798771

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New Directions in Spatial Econometrics by Luc Anselin,Raymond Florax Pdf

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.

Author : Chris Brunsdon,Lex Comber
Publisher : SAGE
Page : 475 pages
File Size : 48,5 Mb
Release : 2014-04-30
Category : Social Science
ISBN : 9781473911192

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An Introduction to R for Spatial Analysis and Mapping by Chris Brunsdon,Lex Comber Pdf

"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.

Author : L. Anselin
Publisher : Springer Science & Business Media
Page : 295 pages
File Size : 44,7 Mb
Release : 2013-03-09
Category : Business & Economics
ISBN : 9789401577991

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Spatial Econometrics: Methods and Models by L. Anselin Pdf

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.

Author : A. Stewart Fotheringham,Chris Brunsdon,Martin Charlton
Publisher : John Wiley & Sons
Page : 282 pages
File Size : 43,8 Mb
Release : 2003-02-21
Category : Science
ISBN : 9780470855256

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Geographically Weighted Regression by A. Stewart Fotheringham,Chris Brunsdon,Martin Charlton Pdf

Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).