Discrete Choice Analysis with R

This book provides a gentle introduction to discrete choice modeling and its practical implementation using the R language. It covers the fundamentals of data and analysis, with examples and code, and emphasizes data visualization to explore input data and model results. It is designed for graduate students, faculty, and researchers conducting empirical work with individual-level choice data.

Format: Hardback
Length: 332 pages
Publication date: 26 January 2023
Publisher: Springer International Publishing AG

This comprehensive book serves as an accessible entry point into the captivating realm of choice modeling and its practical application utilizing the R language. Discrete choice analysis is a versatile family of methods that finds widespread use in studying individual decision-making processes. With robust theoretical underpinnings in consumer behavior, discrete choice models find applications in diverse fields such as health policy, transportation systems, marketing, economics, public policy, political science, urban planning, and criminology, among others. The book assumes no prior knowledge of discrete choice analysis or R, instead presenting both concepts in a intuitive and progressive manner. It is packed with numerous examples and code, guiding readers from basic data operations and the fundamental theory of choice analysis to advanced models such as latent class logit models, mixed logit models, and ordinal logit models with taste heterogeneity. Data visualization is emphasized throughout to facilitate exploration of both input data and model outcomes. This book is of immense interest to graduate students, faculty, and researchers engaged in empirical work with individual-level choice data who are venturing into the field of discrete choice analysis for the first time. Additionally, it appeals to more experienced modelers seeking to explore the potential of R for discrete choice analysis. By integrating the treatment of choice modeling within the R ecosystem, readers gain valuable insights into the broader R family of packages, which encompass data exploration, analysis, and visualization capabilities.

Weight: 699g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031207181
Edition number: 1st ed. 2022