Analysis of Multivariate Social Science Data

✍ Scribed by David J. Bartholomew, Fiona Steele, Jane Galbraith, Irini Moustaki

• Publisher: CRC Press
• Year: 2011
• Tongue: English
• Leaves: 375
• Series: Statistics in the Social and Behavioral Sciences
• Edition: 2nd
• Category: Library

✦ Synopsis

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, confirmatory factor analysis, structural equation models, and multilevel models.
After emphasizing the summarization of data in the first several chapters, the authors focus on regression analysis. This chapter provides a link between the two halves of the book, signaling the move from descriptive to inferential methods and from interdependence to dependence. The remainder of the text deals with model-based methods that primarily make inferences about processes that generate data.

Relying heavily on numerical examples, the authors provide insight into the purpose and working of the methods as well as the interpretation of data. Many of the same examples are used throughout to illustrate connections between the methods. In most chapters, the authors present suggestions for further work that go beyond conventional exercises, encouraging readers to explore new ground in social science research.

Requiring minimal mathematical and statistical knowledge, this book shows how various multivariate methods reveal different aspects of data and thus help answer substantive research questions.

✦ Table of Contents

Front cover
Contents
Preface
CHAPTER 1: Setting the Scene
CHAPTER 2: Cluster Analysis
CHAPTER 3: Multidimensional Scaling
CHAPTER 4: Correspondence Analysis
CHAPTER 5: Principal Components Analysis
CHAPTER 6: Regression Analysis
CHAPTER 7: Factor Analysis
CHAPTER 8: Factor Analysis for Binary Data
CHAPTER 9: Factor Analysis for OrderedCategorical Variables
CHAPTER 10: Latent Class Analysis for Binary Data
CHAPTER 11: Confirmatory Factor Analysis andStructural Equation Models
CHAPTER 12 : Multilevel Modelling
References
Back cover.

✦ Subjects

Social sciences Statistical methods Multivariate analysis MATHEMATICS Applied Probability Statistics General