Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists. Assuming some familiarity with introductory statistics, the book begins by briefly describing a variety of study designs used in the behavioral sciences, and the concept of models for data analysis. The contentious issues of p-values and confidence intervals are also discussed in the introductory chapter.

After describing graphical methods, the book covers regression methods, including simple linear regression, multiple regression, locally weighted regression, generalized linear models, logistic regression, and survival analysis. There are further chapters covering longitudinal data and missing values, before the last seven chapters deal with multivariate analysis, including principal components analysis, factor analysis, multidimensional scaling, correspondence analysis, and cluster analysis.


  • Presents an accessible introduction to multivariate analysis for behavioral scientists
  • Contains a large number of real data sets, including cognitive behavioral therapy, crime rates, and drug usage
  • Includes nearly 100 exercises for course use or self-study
  • Supplemented by a GitHub repository with all datasets and R code for the examples and exercises
  • Theoretical details are separated from the main body of the text
  • Suitable for anyone working in the behavioral sciences with a basic grasp of statistics

chapter 1|21 pages

Data, Measurement, and Models

chapter 2|39 pages

Looking at Data

chapter 4|29 pages

Multiple Linear Regression

chapter 5|10 pages

Generalized Linear Models

chapter 6|15 pages

Applying Logistic Regression

chapter 7|15 pages

Survival Analysis

chapter 11|16 pages

Missing Values

chapter 12|13 pages

Multivariate Data and Multivariate Analysis

chapter 13|28 pages

Principal Components Analysis

chapter 15|24 pages

Exploratory Factor Analysis

chapter 17|23 pages

Cluster Analysis

chapter 18|19 pages

Grouped Multivariate Data