Analyzing Spatial Models Of Choice And Judgment

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Analyzing Spatial Models of Choice and Judgment

Author : David A. Armstrong,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal
Publisher : CRC Press
Page : 302 pages
File Size : 45,6 Mb
Release : 2020-11-16
Category : Mathematics
ISBN : 9781351770507

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Analyzing Spatial Models of Choice and Judgment by David A. Armstrong,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal Pdf

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.

Analyzing Spatial Models of Choice and Judgment with R

Author : David A. Armstrong,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal
Publisher : Unknown
Page : 128 pages
File Size : 52,7 Mb
Release : 2014
Category : Voting
ISBN : 0429185367

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Analyzing Spatial Models of Choice and Judgment with R by David A. Armstrong,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal Pdf

Analyzing Spatial Models of Choice and Judgment with R

Author : David A. Armstrong, II,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal
Publisher : CRC Press
Page : 358 pages
File Size : 41,9 Mb
Release : 2014-02-07
Category : Mathematics
ISBN : 9781466517158

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Analyzing Spatial Models of Choice and Judgment with R by David A. Armstrong, II,Ryan Bakker,Royce Carroll,Christopher Hare,Keith T. Poole,Howard Rosenthal Pdf

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.

Crime Mapping and Spatial Data Analysis using R

Author : Juan Medina Ariza,Reka Solymosi
Publisher : CRC Press
Page : 451 pages
File Size : 40,7 Mb
Release : 2023-04-27
Category : Mathematics
ISBN : 9781000850789

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Crime Mapping and Spatial Data Analysis using R by Juan Medina Ariza,Reka Solymosi Pdf

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.

Generalized Structured Component Analysis

Author : Heungsun Hwang,Yoshio Takane
Publisher : CRC Press
Page : 346 pages
File Size : 41,8 Mb
Release : 2014-12-11
Category : Mathematics
ISBN : 9781466592940

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Generalized Structured Component Analysis by Heungsun Hwang,Yoshio Takane Pdf

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.

Linear Regression Models

Author : John P. Hoffmann
Publisher : CRC Press
Page : 436 pages
File Size : 47,6 Mb
Release : 2021-09-12
Category : Mathematics
ISBN : 9781000437966

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Linear Regression Models by John P. Hoffmann Pdf

Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to determine whether they are satisfied and how to modify the regression model if they are not. The book also includes chapters on specifying the correct model, adjusting for measurement error, understanding the effects of influential observations, and using the model with multilevel data. The concluding chapter presents an alternative model—logistic regression—designed for binary or two-category outcome variables. The book includes appendices that discuss data management and missing data and provides simulations in R to test model assumptions. Features Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied. Uses numerous graphs in R to illustrate the model’s results, assumptions, and other features. Does not assume a background in calculus or linear algebra, rather, an introductory statistics course and familiarity with elementary algebra are sufficient. Provides many examples using real-world datasets relevant to various academic disciplines. Fully integrates the R software environment in its numerous examples. The book is aimed primarily at advanced undergraduate and graduate students in social, behavioral, health sciences, and related disciplines, taking a first course in linear regression. It could also be used for self-study and would make an excellent reference for any researcher in these fields. The R code and detailed examples provided throughout the book equip the reader with an excellent set of tools for conducting research on numerous social and behavioral phenomena. John P. Hoffmann is a professor of sociology at Brigham Young University where he teaches research methods and applied statistics courses and conducts research on substance use and criminal behavior.

Issue Voting and Party Competition

Author : Anna-Sophie Kurella
Publisher : Springer
Page : 147 pages
File Size : 49,5 Mb
Release : 2017-03-15
Category : Political Science
ISBN : 9783319533780

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Issue Voting and Party Competition by Anna-Sophie Kurella Pdf

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.

Ordered Regression Models

Author : Andrew S. Fullerton,Jun Xu
Publisher : CRC Press
Page : 184 pages
File Size : 49,6 Mb
Release : 2016-04-21
Category : Mathematics
ISBN : 9781466569744

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Ordered Regression Models by Andrew S. Fullerton,Jun Xu Pdf

Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives presents regression models for ordinal outcomes, which are variables that have ordered categories but unknown spacing between the categories. The book provides comprehensive coverage of the three major classes of ordered regression models (cumulative, stage, and adjacent) as well as variations based on the application of the parallel regression assumption. The authors first introduce the three "parallel" ordered regression models before covering unconstrained partial, constrained partial, and nonparallel models. They then review existing tests for the parallel regression assumption, propose new variations of several tests, and discuss important practical concerns related to tests of the parallel regression assumption. The book also describes extensions of ordered regression models, including heterogeneous choice models, multilevel ordered models, and the Bayesian approach to ordered regression models. Some chapters include brief examples using Stata and R. This book offers a conceptual framework for understanding ordered regression models based on the probability of interest and the application of the parallel regression assumption. It demonstrates the usefulness of numerous modeling alternatives, showing you how to select the most appropriate model given the type of ordinal outcome and restrictiveness of the parallel assumption for each variable. Web Resource More detailed examples are available on a supplementary website. The site also contains JAGS, R, and Stata codes to estimate the models along with syntax to reproduce the results.

Bayesian Psychometric Modeling

Author : Roy Levy,Robert J. Mislevy
Publisher : CRC Press
Page : 480 pages
File Size : 47,8 Mb
Release : 2017-07-28
Category : Mathematics
ISBN : 9781439884683

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Bayesian Psychometric Modeling by Roy Levy,Robert J. Mislevy Pdf

A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate—and sometimes conflicting—ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.

Multilevel Modeling Using Mplus

Author : Holmes Finch,Jocelyn Bolin
Publisher : CRC Press
Page : 336 pages
File Size : 40,5 Mb
Release : 2017-02-03
Category : Mathematics
ISBN : 9781498748254

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Multilevel Modeling Using Mplus by Holmes Finch,Jocelyn Bolin Pdf

This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts, using Mplus as the software tool, and demonstrating the various functions available for these analyses in Mplus, which is widely used by researchers in various fields, including most of the social sciences. In particular, Mplus offers users a wide array of tools for latent variable modelling, including for multilevel data.

Regression Analysis in R

Author : Jocelyn E. Bolin
Publisher : CRC Press
Page : 193 pages
File Size : 48,5 Mb
Release : 2022-07-27
Category : Mathematics
ISBN : 9781000620245

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Regression Analysis in R by Jocelyn E. Bolin Pdf

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

Multilevel Modeling Using R

Author : W. Holmes Finch,Jocelyn E. Bolin,Ken Kelley
Publisher : CRC Press
Page : 225 pages
File Size : 47,7 Mb
Release : 2016-03-09
Category : Mathematics
ISBN : 9781466515864

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Multilevel Modeling Using R by W. Holmes Finch,Jocelyn E. Bolin,Ken Kelley Pdf

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/

Intensive Longitudinal Analysis of Human Processes

Author : Kathleen M. Gates,Sy-Miin Chow,Peter C. M. Molenaar
Publisher : CRC Press
Page : 260 pages
File Size : 47,8 Mb
Release : 2023-01-31
Category : Mathematics
ISBN : 9781482230604

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Intensive Longitudinal Analysis of Human Processes by Kathleen M. Gates,Sy-Miin Chow,Peter C. M. Molenaar Pdf

This book focuses on a span of statistical topics relevant to researchers who seek to conduct person-specific analysis of human data. Our purpose is to provide one consolidated resource that includes techniques from disciplines such as engineering, physics, statistics, and quantitative psychology and outlines their application to data often seen in human research. The book balances mathematical concepts with information needed for using these statistical approaches in applied settings, such as interpretative caveats and issues to consider when selecting an approach. The statistical topics covered here include foundational material as well as state-of-the-art methods. These analytic approaches can be applied to a range of data types such as psychophysiological, self-report, and passively collected measures such as those obtained from smartphones. We provide examples using varied data sources including functional MRI (fMRI), daily diary, and ecological momentary assessment data. Features: Description of time series, measurement, model building, and network methods for person-specific analysis Discussion of the statistical methods in the context of human research Empirical and simulated data examples used throughout the book R code for analyses and recorded lectures for each chapter available via a link available at www.routledge.com/9781482230598 Across various disciplines of human study, researchers are increasingly seeking to conduct person-specific analysis. This book provides comprehensive information, so no prior knowledge of these methods is required. We aim to reach active researchers who already have some understanding of basic statistical testing. Our book provides a comprehensive resource for those who are just beginning to learn about person-specific analysis as well as those who already conduct such analysis but seek to further deepen their knowledge and learn new tools.

Mixed-Mode Official Surveys

Author : Barry Schouten,Jan van den Brakel,Bart Buelens,Deirdre Giesen,Annemieke Luiten,Vivian Meertens
Publisher : CRC Press
Page : 326 pages
File Size : 47,7 Mb
Release : 2021-09-28
Category : Mathematics
ISBN : 9780429865862

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Mixed-Mode Official Surveys by Barry Schouten,Jan van den Brakel,Bart Buelens,Deirdre Giesen,Annemieke Luiten,Vivian Meertens Pdf

Mixed-mode surveys have become a standard at many statistical institutes. However, the introduction of multiple modes in one design goes with challenges to both methodology and logistics. Mode-specific representation and measurement differences become explicit and demand for solutions in data collection design, questionnaire design, and estimation. This is especially true when surveys are repeated and are input to long time series of official statistics. So how can statistical institutes deal with such changes? What are the origins of mode-specific error? And how can they be dealt with? In this book, the authors provide answers to these questions, and much more. Features Concise introduction to all the key elements of mixed-mode survey design and analysis Realistic official statistics examples from three general population surveys Suitable for survey managers and survey statisticians alike An overview of mode-specific representation and measurement errors and how to avoid, reduce and adjust them

Big Data and Social Science

Author : Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
Publisher : CRC Press
Page : 377 pages
File Size : 46,7 Mb
Release : 2016-09-15
Category : Mathematics
ISBN : 9781498751414

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Big Data and Social Science by Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane Pdf

Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.