Principal Components Analysis

1. Auflage 1989
ISBN: 978-0-8039-3104-6
Verlag: Sage Publications, Inc

Buch, Englisch, Band 69, 96 Seiten, Format (B × H): 140 mm x 216 mm, Gewicht: 135 g

Reihe: Quantitative Applications in the Social Sciences

For anyone in need of a concise, introductory guide to principle components analysis, this book is a must. Through an effective use of simple mathematical geometrical and multiple real-life examples (such as crime statistics, indicators of drug abuse, and educational expenditures)--and by minimizing the use of matrix algebra--the reader can quickly master and put this technique to immediate use. In addition, the author shows how this technique can be used in tandem with other multivariate analysis techniques-such as multiple regression and discriminant analysis.

Flexible in his presentation, Dunteman speaks to students at differing levels, beginning or advanced, bringing them new material that is both accessible and useful.

"Two of the best attributes of the book are the prolific use of good examples--primarily social science based--and the repetition basics. This book is a useful addition to the work in this area."

--Issues in Researching Sexual Behavior

"Most academic researchers and practitioners will benefit from the experience and practical advice in this paper. Not only does Dunteman contribute to our understanding of principal components, but he suggests several good ideas on how to make wider and better use of the technique."

--Journal of Marketing Research

"A concise, introductory guide with a minimal use of matrix algebra and with multiple real-life examples."

--Bulletin de Methodologie Sociologique

"An interesting and useful little book."

--Journal of Classification

Autoren/Hrsg.

Dunteman, George H.

Dunteman, George Henry

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

Introduction
Basic Concepts of Principal Components
Geometrical Properties of Principal Components
Decomposition Properties of Principal Components
Principal Components of Patterned Correlation Matrices
Rotation of Principal Components
Using Principal Components to Select a Subset of Variables
Principal Components Versus Factor Analysis
Uses of Principal Components in Regression Analysis
Using Principal Components to Detect Outlying and Influential Observations
Use of Principal Components in Cluster Analysis
Use of Principal Components Analysis in Conjunction with Other Multivariate Analysis Procedures
Other Techniques Related to Principal Components
Summary and Conclusions