Analyzing Spatial Models of Choice and Judgment with R

Analyzing Spatial Models of Choice and Judgment with R
Author: David A. Armstrong, II
Publisher: CRC Press
Total Pages: 351
Release: 2014-02-07
Genre: Mathematics
ISBN: 1466517166

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.

Analyzing Spatial Models of Choice and Judgment

Analyzing Spatial Models of Choice and Judgment
Author: David A. Armstrong
Publisher: CRC Press
Total Pages: 302
Release: 2020-11-16
Genre: Mathematics
ISBN: 1351770500

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.

Crime Mapping and Spatial Data Analysis using R

Crime Mapping and Spatial Data Analysis using R
Author: Juan Medina Ariza
Publisher: CRC Press
Total Pages: 451
Release: 2023-04-27
Genre: Mathematics
ISBN: 1000850781

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.

Multilevel Modeling Using R

Multilevel Modeling Using R
Author: W. Holmes Finch
Publisher: CRC Press
Total Pages: 225
Release: 2016-03-09
Genre: Mathematics
ISBN: 1466515864

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/

Issue Voting and Party Competition

Issue Voting and Party Competition
Author: Anna-Sophie Kurella
Publisher: Springer
Total Pages: 159
Release: 2017-03-15
Genre: Political Science
ISBN: 3319533789

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.

Generalized Structured Component Analysis

Generalized Structured Component Analysis
Author: Heungsun Hwang
Publisher: CRC Press
Total Pages: 346
Release: 2014-12-11
Genre: Mathematics
ISBN: 146659294X

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.

Regression Analysis in R

Regression Analysis in R
Author: Jocelyn E. Bolin
Publisher: CRC Press
Total Pages: 193
Release: 2022-07-27
Genre: Mathematics
ISBN: 1000620247

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

The Oxford Handbook of Legislative Studies

The Oxford Handbook of Legislative Studies
Author: Shane Martin
Publisher: Oxford University Press, USA
Total Pages: 785
Release: 2014
Genre: Political Science
ISBN: 0199653011

Legislatures are arguably the most important political institution in modern democracies. The Oxford Handbook of Legislative Studies, written by some of the most distinguished legislative scholars in political science, provides a comprehensive and up-to-date description and critical assessment of the state of the art in this key area.

Analytical Theory of Democracy

Analytical Theory of Democracy
Author: Andranik Tangian
Publisher: Springer Nature
Total Pages: 1057
Release: 2020-03-30
Genre: Business & Economics
ISBN: 3030396916

This book operationalizes the idea of political representation, which is fundamental to modern democracies. Both individual representatives and representative bodies are evaluated using the indices of popularity (the average percentage of the population whose opinion is represented on topical policy issues) and universality (the percentage of issues for which the prevailing public opinion is represented). Viewed as objective functions, these indices can aid in the search for optimal representatives and representative bodies. By replacing the consistency analysis of the social choice axioms with the calculation of the best compromises, the paradoxes of social choice, such as those of Condorcet and Arrow, can be overcome. These indices also form the core of an alternative election method that is aimed at enhancing policy representation — a recent concept of political representation, which is not supported by the conventional voting systems shaped during the American and French Revolutions. This method is tested in a series of election experiments that focus on implementation details. In addition, non-societal applications such as MCDM, finance or traffic control are considered, where the objects that reflect the properties or behavior of other objects are regarded as their “representatives.” Given its scope, the book will appeal to political scientists, economists and operations researchers, as well as to politicians interested in improving democratic performance and electoral system design.