Modern Factor Analysis

Author: Harry H. Harman
Publisher: University of Chicago Press
ISBN: 9780226316529
Format: PDF, ePub, Mobi
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Foundations of factor analysis; Direct factor analysis methods; Derived factor solutions; Factor measurements.

An Easy Guide to Factor Analysis

Author: Paul Kline
Publisher: Routledge
ISBN: 1317725603
Format: PDF, ePub
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Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, and concludes with a discussion of the use of the technique with various examples. An Easy Guide to Factor Analysis is the clearest, most comprehensible introduction to factor analysis for students. All those who need to use statistics in psychology and the social sciences will find it invaluable. Paul Kline is Professor of Psychometrics at the University of Exeter. He has been using and teaching factor analysis for thirty years. His previous books include Intelligence: the psychometric view (Routledge 1990) and The Handbook of Psychological Testing (Routledge 1992).

SPSS Step by Step

Author: Cole Davis
Publisher: Policy Press
ISBN: 1447306287
Format: PDF, ePub, Docs
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A logically ordered guide to analysing everyday problems, SPSS Step by Step is distinctive in being both easy to grasp and readable.

Factor Analysis in Chemistry

Author: Edmund R. Malinowski
Publisher: Wiley
ISBN: 9780471134794
Format: PDF, ePub
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Factor analysis is a mathematical tool for examining a wide range of data sets, with applications especially important to the design of experiments (DOE), spectroscopy, chromatography, and chemometrics. Whereas the first two editions concentrated on standardizing the fundamentals of this emerging discipline, the Third Edition of Factor Analysis in Chemistry, the "bible" of factor analysis, proves a comprehensive handbook at a level that is consistent with the research and design of experiments today. With the exception of updates, the introductory chapters remain unchanged. Chapter 6 has been edited to focus on evolutionary methods, including window factor analysis, transmutation, and DECRA. Selections on partial least squares and multimode analysis have been expanded and consolidated into two new chapters, 7 and 8. Some of the latest advances in a wide variety of fields, such as chromatography, NMR, biomedicine, environmental science, food, and fuels, are described in the applications chapters (chapters 9 through 12). Other features of the book include: Provides history of the discipline as well as theory, philosophy, and applications Written for all readership levels: introductory, intermediate, and advanced Explains complicated concepts in simple language without sacrificing mathematical rigor Presents concepts and programs in a style that allows the user to develop programs in any computer language Demonstrates the utility of various factor analytical techniques for solving practical problems in chemistry and related sciences Showcases a unique presentation of partial least squares

Essentials of Multivariate Data Analysis

Author: Neil H. Spencer
Publisher: CRC Press
ISBN: 1466584793
Format: PDF
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Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel® can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book’s CRC Press web page. Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab®, R, SAS, SPSS, and Stata.

Factor Analysis at 100

Author: Robert Cudeck
Publisher: Routledge
ISBN: 1135594031
Format: PDF, ePub, Docs
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Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Because of its importance, a conference was held to mark the centennial of the publication of Charles Spearman's seminal 1904 article which introduced the major elements of this invaluable statistical tool. This book evolved from that conference. It provides a retrospective look at major issues and developments as well as a prospective view of future directions in factor analysis and related methods. In so doing, it demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Featuring an outstanding collection of contributors, this volume offers unique insights on factor analysis and its related methods. Several chapters have a clear historical perspective, while others present new ideas along with historical summaries. In addition, the book reviews some of the extensions of factor analysis to such techniques as latent growth curve models, models for categorical data, and structural equation models. Factor Analysis at 100 will appeal to graduate students and researchers in the behavioral, social, health, and biological sciences who use this technique in their research. A basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.