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.
Statistical Studies of Income, Poverty and Inequality in Europe Computing and Graphics in R using EU-SILC
Latent Markov Models for Longitudinal Data
Foundations of Factor Analysis
Linear Causal Modeling with Structural Equations
Analysis of Multivariate Social Science Data
By Robert O'Brien
August 19, 2014
Develop a Deep Understanding of the Statistical Issues of APC Analysis Age–Period–Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include ...
By Nicholas T. Longford
July 07, 2014
There is no shortage of incentives to study and reduce poverty in our societies. Poverty is studied in economics and political sciences, and population surveys are an important source of information about it. The design and analysis of such surveys is principally a statistical subject matter and ...
By Duanli Yan, Alina A. von Davier, Charles Lewis
May 07, 2014
Devising tests that evaluate a nation’s educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is ...
By Leslie Rutkowski, Matthias von Davier, David Rutkowski
November 12, 2013
Winner of the 2017 AERA Division D Significant Contribution to Educational Measurement and Research Methodology Award! Technological and statistical advances, along with a strong interest in gathering more information about the state of our educational systems, have made it possible to assess more ...
By Michael Smithson, Edgar C. Merkle
September 05, 2013
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences. It incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous ...
By Francesco Bartolucci, Alessio Farcomeni, Fulvia Pennoni
October 29, 2012
Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in ...
By Stanley A Mulaik
September 25, 2009
Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis ...
By Stanley A. Mulaik
June 16, 2009
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In ...
By David J. Bartholomew, Fiona Steele, Jane Galbraith, Irini Moustaki
June 04, 2008
Drawing on the authors’ varied experiences working and teaching in the field, Analysis of Multivariate Social Science Data, Second Editionenables a basic understanding of how to use key multivariate methods in the social sciences. With updates in every chapter, this edition expands its topics to ...
By Michael Greenacre, Jorg Blasius
June 23, 2006
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical ...