This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.

Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.

This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.

Providing basic foundations for measuring inequality from the perspective of distributional properties This monograpg reviews a set of widely used summary inequality measures, and the lesser known relative distribution method provides the basic rationale behind each measure and discusses their interconnections. It also introduces model-based decomposition of inequality over time using quantile regression. This approach enables researchers to estimate two different contributions to changes in inequality between two time points. Key Features Clear statistical explanations provide fundamental statistical basis for understanding the new modeling framework Straightforward empirical examples reinforce statistical knowledge and ready-to-use procedures Multiple approaches to assessing inequality are introduced by starting with the basic distributional property and providing connections among approaches This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as individual researchers.

This book showcases a wealth of knowledge and insight on gender and sexuality development. With contributions from leading researchers, it covers a comprehensive set of topics at the forefront of the field and strikes a balance between traditional and emerging areas of study. Given that gender and sexuality are shaped by myriad influences, this book is modelled on an interdisciplinary perspective and delves into biological, comparative, psychological, cognitive, social, cultural, and clinical approaches. In so doing, this collection conveys the rich tapestry of gender and sexuality science and will hold value for many. For those already in the field, this book provides an excellent resource for brushing up on the latest and for inspiring the next phases of scientific investigation. Those who are newer to the field, including undergraduate and graduate students, stand to gain tremendously from not only the thoughtful and informative content, but also from the interdisciplinary approach modelled throughout the book. Beyond academia, this book is a valuable resource for clinicians and policy makers who deal with child and adolescent issues.

Providing an authoritative guide to theory and method, the key sub-disciplines and the primary debates in contemporary sociology, this work brings together the leading authors to reflect on the condition of the discipline.

Volume 24 offers fresh theoretical and methodological insights into the key issues in the field of economic inequality.

This book examines extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most renowned international experts in the field. They cover topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education.

An incomparably useful examination of statistical methods for comparison The nature of doing science, be it natural or social, inevitably calls for comparison. Statistical methods are at the heart of such comparison, for they not only help us gain understanding of the world around us but often define how our research is to be carried out. The need to compare between groups is best exemplified by experiments, which have clearly defined statistical methods. However, true experiments are not always possible. What complicates the matter more is a great deal of diversity in factors that are not independent of the outcome. Statistical Group Comparison brings together a broad range of statistical methods for comparison developed over recent years. The book covers a wide spectrum of topics from the simplest comparison of two means or rates to more recently developed statistics including double generalized linear models and Bayesian as well as hierarchical methods. Coverage includes: * Testing parameter equality in linear regression and other generalized linear models (GLMs), in order of increasing complexity * Likelihood ratio, Wald, and Lagrange multiplier statistics examined where applicable * Group comparisons involving latent variables in structural equation modeling * Models of comparison for categorical latent variables Examples are drawn from the social, political, economic, and biomedical sciences; many can be implemented using widely available software. Because of the range and the generality of the statistical methods covered, researchers across many disciplines-beyond the social, political, economic, and biomedical sciences-will find the book a convenient reference for many a research situation where comparisons may come naturally.