Preface
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
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

Additional examples and further work
Multidimensional scaling

Sample chapter: 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

Additional examples and further work
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: confidence in purchasing from European Community countries Correspondence analysis of multiway tables

Additional examples and further work
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 the original variables

Additional examples and further work
Regression analysis

Basic ideas

Simple linear regression

A probability model for simple linear regression

Inference for the simple linear regression model

Checking the assumptions

Multiple regression

Examples of multiple regression

Estimation and inference about the parameters

Interpretation of the regression coefficients

Selection of regressor variables

Transformations and interactions

Logistic regression

Path analysis

Additional examples and further work
Factor analysis

Introduction to latent variable models

The linear singlefactor 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 components analysis

Additional examples and further work

Software
Factor analysis for binary data

Sample chapter: 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 using the item response theory approach

Goodnessoffit

Factor scores

Rotation

Underlying variable approach

Example: sexual attitudes

Additional examples and further work

Software
Factor analysis for ordered categorical variables

The practical background

Two approaches to modeling ordered categorical data

Item response function approach

Examples

The underlying variable approach

Unordered and partially ordered observed variables

Additional examples and further work

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

Additional examples and further work

Software
Confirmatory factor analysis and structural equation models

Introduction

Path diagram

Measurement models

Adequacy of the model

Introduction to structural equation models with latent variables

The linear structural equation model

A worked example

Extensions

Additional examples

Software
Multilevel modelling

Introduction

Some potential applications

Comparing groups using multilevel modelling

Random intercept model

Random slope model

Contextual effects

Multilevel multivariate regression

Multilevel factor analysis

Additional examples and further work

Further topics

Estimation procedures and software
References
Index
Further reading sections appear at the end of each chapter.