Large and complex datasets are becoming prevalent in the social and behavioral sciences and statistical methods are crucial for the analysis and interpretation of such data. This series aims to capture new developments in statistical methodology with particular relevance to applications in the social and behavioral sciences. It seeks to promote appropriate use of statistical, econometric and psychometric methods in these applied sciences by publishing a broad range of reference works, textbooks and handbooks.
The scope of the series is wide, including applications of statistical methodology in sociology, psychology, economics, education, marketing research, political science, criminology, public policy, demography, survey methodology and official statistics. The titles included in the series are designed to appeal to applied statisticians, as well as students, researchers and practitioners from the above disciplines. The inclusion of real examples and case studies is therefore essential.
Please contact us if you have an idea for a book for the series.
By Rudolf Debelak, Carolin Strobl, Matthew D. Zeigenfuse
June 07, 2022
An Introduction to the Rasch Model with Examples in R offers a clear, comprehensive introduction to the Rasch model along with practical examples in the free, open-source software R. It is accessible for readers without a background in psychometrics or statistics, while also providing detailed ...
By John P. Hoffmann
September 13, 2021
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...
By Ryan Kennedy, Philip D. Waggoner
March 09, 2021
Introduction to R for Social Scientists: A Tidy Programming Approach introduces the Tidy approach to programming in R for social science research to help quantitative researchers develop a modern technical toolbox. The Tidy approach is built around consistent syntax, common grammar, and stacked ...
Edited
By Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane
November 18, 2020
Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer ...
By Ole J. Forsberg
September 29, 2020
Elections are random events. From individuals deciding whether to vote, to people deciding for whom to vote, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day…or beyond. Understanding Elections through Statistics: ...
By Klaas Sijtsma, L. Andries van der Ark
October 23, 2020
Despite the overwhelming use of tests and questionnaires, the psychometric models for constructing these instruments are often poorly understood, leading to suboptimal measurement. Measurement Models for Psychological Attributes is a comprehensive and accessible treatment of the common and the less...
Edited
By Kristen Olson, Jolene D. Smyth, Jennifer Dykema, Allyson L. Holbrook, Frauke Kreuter, Brady T. West
May 21, 2020
Interviewer Effects from a Total Survey Error Perspective presents a comprehensive collection of state-of-the-art research on interviewer-administered survey data collection. Interviewers play an essential role in the collection of the high-quality survey data used to learn about our society and ...
Edited
By Duanli Yan, André A. Rupp, Peter W. Foltz
March 09, 2020
"Automated scoring engines […] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have ...
By Robert P. Haining, Guangquan Li
February 07, 2020
Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with small-area spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear ...
By Dato N. M. de Gruijter, Leo J. Th. van der Kamp
September 05, 2019
Since the development of the first intelligence test in the early 20th century, educational and psychological tests have become important measurement techniques to quantify human behavior. Focusing on this ubiquitous yet fruitful area of research, Statistical Test Theory for the Behavioral Sciences...
By W. Holmes Finch, Jocelyn E. Bolin, Ken Kelley
May 20, 2019
Like its bestselling predecessor, Multilevel Modeling Using R, Second Edition provides the reader with 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...
Edited
By Li-Chun Zhang, Raymond L. Chambers
May 08, 2019
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable ...