This edited book is the first one in English that demonstrates the innovative use of cutting-edge statistical methods for sociological and social science data. Unlike books that focus solely on applying quantitative methods to sociological and social science data, this book includes in-depth methodological discussions that highlight the interplay between sociological theory and data analysis. With expertise in sociology, psychology, social statistics, and survey methods and data collection, researchers in quantitative social science have developed extended, improved methods such as multivariate statistical analysis, survey methods, cluster analysis, multidimensional scaling, correspondence analysis, latent state model, network analysis, and other means tailored for cross-sectional, longitudinal, compositional, and network data to contribute to solving society's greatest challenges. The purpose of the book is twofold. One is to represent studies focusing on new directions in statistical analysis of sociological and social science data. These new directions may include novel theoretical paradigms, developing topical areas of research, innovative methodologies, and/or substantive findings that explore social processes. The other is to offer the most appropriate models and methods for explaining social phenomena and their underlying structures with the goal of discovering useful information, drawing conclusions, and supporting decision-making. The methodological discussions empower researchers to make informed decisions about research design, data collection, and analysis, enhancing the quality and validity of their sociological inquiries.

Provides innovative use of cutting-edge statistical methods for sociological and social science data Combines quantitative methods and applications with discussions of quantitative methods to analyze sociological data Presents a wide range of fields to which quantitative methods can be applied to solve society's challenges

Autorentext
Miki Nakai is Professor of Sociology in the College of Social Sciences at Ritsumeikan University. Her research interests include gender stratification or inequality, the analysis of survey data, the processes of inequalities, life course theory and methods.

Inhalt

Preface.- Foreword.- 1 Modeling the structure of social phenomena.- 2 Discrete latent variable models.- 3 High-dimensional data analysis.- 4 Approaches to analysis with missing data.- 5 Longitudinal data analysis.- 6 Attitudinal data analysis.- 7 Time series and cross-national comparisons of occupational segregation.- 8 Visualization of social mechanisms.- 9 Statistical approaches to the characteristics of the occupational structure.