The Analysis and Interpretation of Multivariate Data for Social Scientists

SETTING THE SCENE
Structure of the Book
Our Limited Use of Mathematics
Variables
The Geometry of Multivariate Analysis
Use of Examples
Data Inspection, Transformations, and Missing Data
A Final Word
Reading
CLUSTER ANALYSIS
Classification in Social Sciences
Some Methods of Cluster Analysis
Graphical Presentation of Results
Derivation of the Distance Matrix
Example on English Dialects
Comparisons
Clustering Variables
MULTIDIMENSIONAL SCALING
Introduction
Examples
Classical, Ordinal and Metrical Multidimensional Scaling
Comments on Computational Procedures
Assessing Fit and Choosing the Number of Dimensions
A Worked Example: Dimensions of Colour Vision
CORRESPONDENCE ANALYSIS
Aims of Correspondence Analysis
Carrying Out a Correspondence Analysis : A Simple Numerical Example
Carrying Out a Correspondence Analysis: The General Method
The Biplot
Interpretation of Dimensions
Choosing the Number of Dimensions
Example: Purchasing from European Community Countries
Correspondence Analysis of Multi-Way Tables
PRINCIPAL COMPONENTS ANALYSIS
Introduction
Some Potential Applications
Illustration of PCA for Two Variables
An Outline of PCA
Examples
Component Scores
The Link Between PCA and Multidimensional Scaling and Between PCA and Correspondence Analysis
Using Principal Component Scores to Replace Original Variables
FACTOR ANALYSIS
Introduction to Latent Variable Models
The Linear Single-Factor Model
The General Linear Factor Model
Interpretation
Adequacy of the Model and Choice of the Number of Factors
Rotation
Factor Scores
A Worked Example: The Test Anxiety Inventory
How Rotation Helps Interpretation
A Comparison of Factor Analysis and Principal Component Analysis
FACTOR ANALYSIS FOR BINARY DATA
Latent Trait Models
Why is the Factor Analysis Model for Metrical Variables Invalid for Binary Responses?
Factor Model for Binary Data
Goodness-of-Fit
Factor Scores
Rotation
Underlying Variable Approach
Example: Sexual Attitudes
Software
FACTOR ANALYSIS FOR ORDERED CATEGORICAL VARIABLES
The Practical Background
Two Approaches to Modelling Ordered Categorical Data
Item Response Function Approach
Examples
The Underlying Variable Approach
Unordered and Partially Ordered Observed Variables
Software
LATENT CLASS ANALYSIS FOR BINARY DATA
Introduction
The Latent Class Model for Binary Data
Example: Attitude to Science and Technology Data
How can we Distinguish the Latent Class Model from the Latent Trait Model?
Latent Class Analysis, Cluster Analysis, and Latent Profile Analysis
Software
REFERENCES
INDEX

Each chapter also contains sections of "Further Examples and Suggestions for Further Wor" and "Further Reading."