Approaching Multivariate Analysis, 2nd Edition (2^nd Ed.)
A Practical Introduction

This fully updated new edition not only provides an introduction to a range of advanced statistical techniques that are used in psychology, but has been expanded to include new chapters describing methods and examples of particular interest to medical researchers. It takes a very practical approach, aimed at enabling readers to begin using the methods to tackle their own problems.

This book provides a non-mathematical introduction to multivariate methods, with an emphasis on helping the reader gain an intuitive understanding of what each method is for, what it does and how it does it. The first chapter briefly reviews the main concepts of univariate and bivariate methods and provides an overview of the multivariate methods that will be discussed, bringing out the relationships among them, and summarising how to recognise what types of problem each of them may be appropriate for tackling. In the remaining chapters, introductions to the methods and important conceptual points are followed by the presentation of typical applications from psychology and medicine, using examples with fabricated data.

Instructions on how to do the analyses and how to make sense of the results are fully illustrated with dialogue boxes and output tables from SPSS, as well as details of how to interpret and report the output, and extracts of SPSS syntax and code from relevant SAS procedures.

This book gets students started, and prepares them to approach more comprehensive treatments with confidence. This makes it an ideal text for psychology students, medical students and students or academics in any discipline that uses multivariate methods.

Preface. 1. Multivariate Techniques in Context. 2. Analysis of Variance (ANOVA). 3. Multivariate Analysis of Variance (MANOVA). 4. Multiple Regression. 5. Analysis of covariance (ANCOVA). 6. Partial Correlation, Mediation and Moderation. 7. Path Analysis. 8. Factor Analysis. 9. Discriminant Analysis and Logistic Regression. 10. Cluster Analysis. 11. Multidimensional Scaling. 12. Loglinear Models. 13. Poisson Regression. 14. Survival Analysis. 15. Longitudinal Data. Appendix: SPSS and SAS Syntax.

Pat Dugard worked until 1999 at the University of Abertay Dundee teaching statistics and providing statistical support and consultancy for researchers in psychology, engineering and other areas. Since then she has worked on two books with John Todman, with Open University and WEA students, and done statistical work for community groups and for engineers at Abertay.

John Todman lectured in the Psychology Department at the University of Dundee, first as a Lecturer, then as Senior Lecturer, then as a Professor. During that period he taught in addition to aspects of cognitive psychology, Design and Analysis at undergraduate and postgraduate levels. His research has been primarily in the areas of computer-aided communication for people without speech, and in computer anxiety. Sadly, John died just as this edition of the book had been completed.

Harry Staines has lectured statistics to a wide variety of students (including psychologists and nurses), led research groups and supervised postgraduate research students at the University of Abertay Dundee for over 20 years. He left his job as Professor of Applied Statistics in 2007 to work in the pharmaceutical industry designing and analyzing clinical trials. He also provides statistical support to medical researchers and QCMD.