Statistical Factor Analysis and Related Methods Theory and Applications

  • ISBN13:


  • ISBN10:


  • Edition: 1st
  • Format: eBook
  • Copyright: 2007-12-17
  • Publisher: Wiley-Interscience

Note: Supplemental materials are not guaranteed with Rental or Used book purchases.

Purchase Benefits

  • Free Shipping On Orders Over $35!
    Your order must be $35 or more to qualify for free economy shipping. Bulk sales, PO's, Marketplace items, eBooks and apparel do not qualify for this offer.
  • Get Rewarded for Ordering Your Textbooks! Enroll Now
List Price: $154.66 Save up to $15.47
  • Rent Book $139.19
    Add to Cart Free Shipping


Supplemental Materials

What is included with this book?

  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
  • The Rental copy of this book is not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.


Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory of factor analysis, this new work represents the first unified treatment of the theory and practice of factor analysis and latent variable models. It focuses on such areas as:
* The classical principal components model and sample-population inference
* Several extensions and modifications of principal components, including Q and three-mode analysis and principal components in the complex domain
* Maximum likelihood and weighted factor models, factor identification, factor rotation, and the estimation of factor scores
* The use of factor models in conjunction with various types of data including time series, spatial data, rank orders, and nominal variable
* Applications of factor models to the estimation of functional forms and to least squares of regression estimators

Author Biography

About the author ALEXANDER BASILEVSKY is Professor of Mathematics and Statistics at the University of Winnipeg. He frequently serves as a professional consultant to both government and industry. In addition to numerous scholarly papers and government reports, Professor Basilevsky is the author of Applied Matrix Algebra in Statistical Sciences and coauthor of An Analysis of the U.S. Income Maintenance Experiments. He is a member of the Canadian Statistical Association, the American Statistical Association, and the Statistical Association of Manitoba, of which he is former president-at-large. Professor Basilevsky received his PhD in statistics/econometrics from the University of Southampton, England.

Table of Contents


Matrixes, Vector Spaces.

The Ordinary Principal Components Model.

Statistical Testing of the Ordinary Principal Components Model.

Extensions of the Ordinary Principal Components Model.

Factor Analysis.

Factor Analysis of Correlated Observations.

Ordinal and Nominal Random Data.

Other Models for Discrete Data.

Factor Analysis and Least Squares Regression.




Rewards Program

Write a Review