Analyzing Spatial Models of Choice and Judgment

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.

1. Introduction The Spatial Theory of Voting Theoretical Development and Applications of the Spatial Voting Model The Development of Empirical Estimation Methods for Spatial Models of Voting The Basic Space Theory Summary of Data Types Analyzed by Spatial Voting Models Conclusion 2. Analyzing Issue Scales Aldrich-McKelvey Scaling The basicspace Package in R Example : European Election Study (French Module) Example : American National Election Study Urban Unrest and Vietnam War Scales Estimating Bootstrapped Standard Errors for Aldrich- McKelvey Scaling Basic Space Scaling: The blackbox Function Example : Convention Delegate Study Example : Swedish Parliamentary Candidate Survey Estimating Bootstrapped Standard Errors for Black Box Scaling Basic Space Scaling: The blackbox transpose Function Example : and Comparative Study of Electoral Systems (Mexican Modules) Estimating Bootstrapped Standard Errors for Black Box Transpose Scaling Using the blackbox transpose Function on Datasets Ordered Optimal Classi_cation Using Anchoring Vignettes Conclusion Exercises 3. Analyzing Similarities and Dissimilarities Data Classical Metric Multidimensional Scaling Example : Nations Similarities Data Metric MDS Using Numerical Optimization Metric MDS Using Majorization (SMACOF) The smacof Package in R Non-Metric Multidimensional Scaling Example : Nations Similarities Data Example : th US Senate Agreement Scores Individual Di_erences Multidimensional Scaling Example : European Election Study (French Module) Conclusion Exercises 4. Unfolding Analysis of Rating Scale Data Solving the Thermometers Problem Metric Unfolding Using the MLSMU Procedure Example : Interest Group Ratings of US Senators Data Metric Unfolding Using Majorization (SMACOF) Example : European Election Study (Danish Module) Comparing the MLSMU and SMACOF Metric Unfolding Procedures Conclusion Exercises 5. Unfolding Analysis of Binary Choice Data The Geometry of Legislative Voting Reading Legislative Roll Call Data into R with the pscl Package Parametric Methods - NOMINATE Obtaining Uncertainty Estimates with the Parametric Bootstrap Types of NOMINATE Scores Accessing DW-NOMINATE Scores The wnominate Package in R Example : The th US House Example : The First European Parliament (Using the Parametric Bootstrap) Nonparametric Methods - Optimal Classi_cation The oc Package in R Example : The French National Assembly during the Fourth Republic Example : American National Election Study Feeling Thermometers Data Conclusion: Comparing Methods for the Analysis of Legislative Roll Call Data Identi_cation of the Model Parameters Comparing Ideal Point Estimates for the th US Senate Exercises 6. Bayesian Scaling Models Bayesian Aldrich-McKelvey Scaling Comparing Aldrich-McKelvey Standard Errors Bayesian Multidimensional Scaling Example : Nations Similarities Data Bayesian Multidimensional Unfolding Example : American National Election Study Feeling Thermometers Data Parametric Methods - Bayesian Item Response Theory The MCMCpack and pscl Packages in R Example : The Term of the US Supreme Court (Unidimensional IRT) Running Multiple Markov Chains in MCMCpack and pscl Example : The Con_rmation Vote of Robert Bork to the US Supreme Court (Unidimensional IRT) Example : The th US Senate (Multidimensional IRT) Identi_cation of the Model Parameters MCMC or a-NOMINATE The anominate Package in R Ordinal and Dynamic IRT Models IRT with Ordinal Choice Data Dynamic IRT EM IRT Conclusion Exercises

Dave Armstrong (http://quantoid.net) is Canada Research Chair in Political Methodology and Associate Professor of Political Science at Western University in Ontario, Canada. He received a Ph.D. in Government and Politics from the University of Maryland in 2009 and was a post-doctoral fellow in the Department of Politics and Nuffield College at the University of Oxford. His research interests revolve around measurement and the relationship between Democracy and state repressive action. His research has been published in the American Political Science Review, the American Journal of Political Science, the American Sociological Review and the R Journal among others. Dave is an active R user and maintainer of a number of packages. DAMisc has a number of functions that ease interpretation and presentation of GLMs. Ryan Bakker is Reader in Comparative Politics at the University of Essex. He received his Ph.D. in Political Science from the University of North Carolina at Chapel Hill in 2007. His research and teaching interests include applied Bayesian modeling, measurement, Western European politics, and EU elections and political parties. He is a principal investigator for the Chapel Hill Expert Survey (CHES), which measures political party positions on a variety of policy-specific issues in the European Union. His work has appeared in Political Analysis, Electoral Studies, European Union Politics, and Party Politics. Royce Carroll is Professor in Comparative Politics at the University of Essex, where he teaches graduate and undergraduate courses on comparative politics and American politics. He received his Ph.D. in Political Science at the University of California, San Diego in 2007. In addition to political methodology, his research focuses on comparative politics of legislatures, coalitions and political parties, as well as measurement of ideology. Carroll is also Director of the Essex Summer School in Social Science Data Analysis. Keith T. Poole is Philip H. Alston Jr. Distinguished Professor, Department of Political Science, University of Georgia. He received his Ph.D. in Political Science from the University of Rochester in 1978. His research interests include methodology, political-economic history of American institutions, economic growth and entrepreneurship, and the political-economic history of railroads. He is the author or coauthor of over 50 articles as well as the author of multiple books. He was a Fellow of the Center for Advanced Study in Behavioral Sciences 2003-2004 and was elected to the American Academy of Arts and Sciences in 2006. Howard Rosenthal is Professor of Politics at NYU and Roger Williams Straus Professor of Social Sciences, Emeritus, at Princeton. Rosenthal's coauthored books include Political Bubbles: Financial Crises and the Failure of American Democracy, Polarized America: The Dance of Ideology and Unequal Riches, Ideology and Congress, and Prediction Analysis of Cross Classifications. He has coedited "What Do We Owe Each Other?" and "Credit Markets for the Poor." Rosenthal is a member of the American Academy of Arts and Sciences. He has been a Fellow of the Center for Advanced Study in Behavioral Sciences and a Visiting Scholar at the Russell Sage Foundation.