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Author : David A. Armstrong
Publisher :
ISBN 13 : 9780429185366
Total Pages : pages
Book Rating : 4.67/5 ( download)
Download or read book Analyzing Spatial Models of Choice and Judgment with R written by David A. Armstrong and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David A. Armstrong
Publisher : CRC Press
ISBN 13 : 1351770500
Total Pages : 302 pages
Book Rating : 4.07/5 ( download)
Download or read book Analyzing Spatial Models of Choice and Judgment written by David A. Armstrong and published by CRC Press. This book was released on 2020-11-16 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent advances in computing power and the widespread availability of preference, perception and choice data, such as public opinion surveys and legislative voting, the empirical estimation of spatial models using scaling and ideal point estimation methods has never been more accessible.The second edition of Analyzing Spatial Models of Choice and Judgment demonstrates how to estimate and interpret spatial models with a variety of methods using the open-source programming language R. Requiring only basic knowledge of R, the book enables social science researchers to apply the methods to their own data. Also suitable for experienced methodologists, it presents the latest methods for modeling the distances between points. The authors explain the basic theory behind empirical spatial models, then illustrate the estimation technique behind implementing each method, exploring the advantages and limitations while providing visualizations to understand the results. This second edition updates and expands the methods and software discussed in the first edition, including new coverage of methods for ordinal data and anchoring vignettes in surveys, as well as an entire chapter dedicated to Bayesian methods. The second edition is made easier to use by the inclusion of an R package, which provides all data and functions used in the book. David A. Armstrong II is Canada Research Chair in Political Methodology and Associate Professor of Political Science at Western University. His research interests include measurement, Democracy and state repressive action. Ryan Bakker is Reader in Comparative Politics at the University of Essex. His research interests include applied Bayesian modeling, measurement, Western European politics, and EU politics. Royce Carroll is Professor in Comparative Politics at the University of Essex. His research focuses on measurement of ideology and the comparative politics of legislatures and political parties. Christopher Hare is Assistant Professor in Political Science at the University of California, Davis. His research focuses on ideology and voting behavior in US politics, political polarization, and measurement. Keith T. Poole is Philip H. Alston Jr. Distinguished Professor of Political Science at the University of Georgia. His research interests include methodology, US political-economic history, economic growth and entrepreneurship. Howard Rosenthal is Professor of Politics at NYU and Roger Williams Straus Professor of Social Sciences, Emeritus, at Princeton. Rosenthal’s research focuses on political economy, American politics and methodology.
Author : David A. Armstrong, II
Publisher : CRC Press
ISBN 13 : 1466517158
Total Pages : 358 pages
Book Rating : 4.58/5 ( download)
Download or read book Analyzing Spatial Models of Choice and Judgment with R written by David A. Armstrong, II and published by CRC Press. This book was released on 2014-02-07 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Methods for Evaluating Your Social Science Data With recent advances in computing power and the widespread availability of political choice data, such as legislative roll call and public opinion survey data, the empirical estimation of spatial models has never been easier or more popular. Analyzing Spatial Models of Choice and Judgment with R demonstrates how to estimate and interpret spatial models using a variety of methods with the popular, open-source programming language R. Requiring basic knowledge of R, the book enables researchers to apply the methods to their own data. Also suitable for expert methodologists, it presents the latest methods for modeling the distances between points—not the locations of the points themselves. This distinction has important implications for understanding scaling results, particularly how uncertainty spreads throughout the entire point configuration and how results are identified. In each chapter, the authors explain the basic theory behind the spatial model, then illustrate the estimation techniques and explore their historical development, and finally discuss the advantages and limitations of the methods. They also demonstrate step by step how to implement each method using R with actual datasets. The R code and datasets are available on the book’s website.
Author : Juan Medina Ariza
Publisher : CRC Press
ISBN 13 : 1000850781
Total Pages : 451 pages
Book Rating : 4.89/5 ( download)
Download or read book Crime Mapping and Spatial Data Analysis using R written by Juan Medina Ariza and published by CRC Press. This book was released on 2023-04-27 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis. This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis. It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis. It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence. In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data. We then introduce a series of tools to study spatial homogeneity and dependence. A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation. The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space. In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
Author : W. Holmes Finch
Publisher : CRC Press
ISBN 13 : 1466515864
Total Pages : 225 pages
Book Rating : 4.64/5 ( download)
Download or read book Multilevel Modeling Using R written by W. Holmes Finch and published by CRC Press. This book was released on 2016-03-09 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modelling using R provides a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. Complete data sets for the book can be found on the book's website www.mlminr.com/
Author : David A. Armstrong, II
Publisher : CRC Press
ISBN 13 : 1466517166
Total Pages : 351 pages
Book Rating : 4.65/5 ( download)
Download or read book Analyzing Spatial Models of Choice and Judgment with R written by David A. Armstrong, II and published by CRC Press. This book was released on 2014-02-07 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Methods for Evaluating Your Social Science Data With recent advances in computing power and the widespread availability of political choice data, such as legislative roll call and public opinion survey data, the empirical estimation of spatial models has never been easier or more popular. Analyzing Spatial Models of Choice and Judgment with R demonstrates how to estimate and interpret spatial models using a variety of methods with the popular, open-source programming language R. Requiring basic knowledge of R, the book enables researchers to apply the methods to their own data. Also suitable for expert methodologists, it presents the latest methods for modeling the distances between points—not the locations of the points themselves. This distinction has important implications for understanding scaling results, particularly how uncertainty spreads throughout the entire point configuration and how results are identified. In each chapter, the authors explain the basic theory behind the spatial model, then illustrate the estimation techniques and explore their historical development, and finally discuss the advantages and limitations of the methods. They also demonstrate step by step how to implement each method using R with actual datasets. The R code and datasets are available on the book’s website.
Author : Anna-Sophie Kurella
Publisher : Springer
ISBN 13 : 3319533789
Total Pages : 147 pages
Book Rating : 4.80/5 ( download)
Download or read book Issue Voting and Party Competition written by Anna-Sophie Kurella and published by Springer. This book was released on 2017-03-15 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines how social cleavage lines shape issue voting and party competition. Based on a study of German elections between 1980 and 1994, it analyzes whether cleavage group members put more weight on policies that address their personal self-interest than voters who are not affected by the cleavage line. Furthermore, it analyzes the consequences of cleavage groups’ deviating patterns of voting behavior for the formal game of party competition. More concretely, the author asks whether equilibrium positions of parties within the policy space are pulled away from the mean due to the more extreme policy demands of cleavage groups in the electorate.
Author : Heungsun Hwang
Publisher : CRC Press
ISBN 13 : 146659294X
Total Pages : 346 pages
Book Rating : 4.40/5 ( download)
Download or read book Generalized Structured Component Analysis written by Heungsun Hwang and published by CRC Press. This book was released on 2014-12-11 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new approach and apply it to their own research. The book emphasizes conceptual discussions throughout while relegating more technical intricacies to the chapter appendices. Most chapters compare generalized structured component analysis to partial least squares path modeling to show how the two component-based approaches differ when addressing an identical issue. The authors also offer a free, online software program (GeSCA) and an Excel-based software program (XLSTAT) for implementing the basic features of generalized structured component analysis.
Author : Jocelyn E. Bolin
Publisher : CRC Press
ISBN 13 : 1000620247
Total Pages : 193 pages
Book Rating : 4.45/5 ( download)
Download or read book Regression Analysis in R written by Jocelyn E. Bolin and published by CRC Press. This book was released on 2022-07-27 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples. Key Features: Full output examples complete with interpretation Full syntax examples to help teach R code Appendix explaining basic R functions Methods for multilevel data that are often included in basic regression texts End of Chapter Comprehension Exercises
Author : Paul M. W. Hackett
Publisher : Frontiers Media SA
ISBN 13 : 2889631087
Total Pages : 104 pages
Book Rating : 4.87/5 ( download)
Download or read book Advances in Facet Theory Research: Developments in Theory, Application and Related Approaches written by Paul M. W. Hackett and published by Frontiers Media SA. This book was released on 2019-11-01 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this Research Topic the two editors bring together a series of articles that use facet theory and allied approaches to research. Since its inception in the work of Louis Guttman in the mid twentieth century, facet theory has become an established approach within social science research. In addition, over the past 70 years a wide range of research publications have appeared operating within the theoretical and analytic rubric of facet theory and for the last two decades a biennial international conference has been held devoted to facet theory research. When using a facet theory approach, an implicit aim of the research within this framework is to bring together in an explicit manner a clear definition of the content area that is being investigated along with data analysis procedures. Integrating the explicit design of research content (for example, attitudes, values, etc) and its subsequent analysis (for example to identify the variables that are influential to respondents in relation to the specific area under investigation) allows for the construction of theory relating to the content area and for the meaningful measurement of complex research areas. The clear explication of an area of research content, is achieved through the use of a mapping sentence (MS). In a MS all of the pertinent variables (called facets) associated with the specific subject matter of the research study are specified in the form of a natural language sentence where facets (variables) are arrange to demonstrate how these theoretically relate to each other. Sub-levels of facets are defined in such a way as to capture the relationships of research variables (facets) to each other and the overall research domain. Background variables are also stated in the MS along with a specified range over which observations will be made to test the veracity of the structural hypotheses (statements regarding the proposed manner in which variables are related to the study’s content) implicit in the MS. Furthermore, by using a MS the researcher is able to select variables that appropriately address the area of content. Traditionally, facet theory has been used in quantitative research but has recently been applied to the analysis of qualitative and philosophical research which incorporates a declarative mapping sentence in such research and which is included in this Research Topic. In order to interrogate these structural hypotheses, quantitative data analysis procedures are employed, such as Smallest Space Analysis (SSA) and Partial Order Scalogram Analysis by base Coordinates (POSAC). In SSA the structure of the content area of interest (the variables that have been included in the MS) can be interrogated as observations that have been made along the specified outcome range, are represented geometrically (as partitioned regions) in a concept-space related to the specific research domain. Individual respondents may also be investigated in terms of their profile of facet related scores using POSAC. A similar approach is employed when analysing information from qualitative facet theory research, which interrogates the structural hypotheses present in the declarative mapping sentence through approaches such as content and narrative analyses. This Research Topic presents work from scholars with particular emphasis upon how the approach has developed both theoretically and in terms of its application, new areas of application, and advances in theory development.
