Analyzing spatial models of choice and judgment with R

Table of content

1 Introduction
2 Analyzing Issue Scales
3 Analyzing Similarities and Dissimilarities Data
4 Unfolding Analysis of Rating Scale Data
5 Unfolding Analysis of Binary Choice Data
6 Bayesian Scaling Models

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.

https://www.routledge.com/Analyzing-Spatial-Models-of-Choice-and-Judgment/Armstrong-Bakker-Carroll-Hare-Poole-Rosenthal/p/book/9781138715332