Enabling a basic understanding of how to use key multivariate methods in the social sciences, this updated edition contains three new chapters on regression analysis, confirmatory factor analysis and structural equation models, and multilevel models. It presents many examples of real-world applications, including voting preferences, social attitudes, educational test scores, and recidivism; covers methods that summarize, describe, and explore multivariate data sets; and establishes a unified approach to latent variable modeling. Full versions of all the data sets in the text, software for performing latent variable analyses, and instructions for implementing the analyses are available on the book's website.

Autorentext

David J. Bartholomew, Fiona Steele, Fiona Steele, Irini Moustaki

Zusammenfassung
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 include regression analysis, con

Inhalt

Preface. Setting the Scene.Cluster Analysis.Multidimensional Scaling.Correspondence Analysis.Principal Components Analysis.Regression Analysis.Factor Analysis.Factor Analysis for Binary Data. Factor Analysis for Ordered Categorical Variables.Latent Class Analysis for Binary Data. Confirmatory Factor Analysis and Structural Equation Models.Multilevel Modeling. References. Index.