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Author : G. Rodriguez
Publisher :
ISBN 13 :
Total Pages : 4 pages
Book Rating : 4.:/5 (897 download)
Download or read book A Canonical Reduction of the Factor Analysis Model written by G. Rodriguez and published by . This book was released on 1975 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : G. David Garson
Publisher : Taylor & Francis
ISBN 13 : 1000810593
Total Pages : 547 pages
Book Rating : 4.0/5 (8 download)
Download or read book Factor Analysis and Dimension Reduction in R written by G. David Garson and published by Taylor & Francis. This book was released on 2022-12-16 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book’s coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.
Author : Stanley A. Mulaik
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 490 pages
Book Rating : 4.F/5 ( download)
Download or read book The Foundations of Factor Analysis written by Stanley A. Mulaik and published by McGraw-Hill Companies. This book was released on 1971 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Raja Velu
Publisher : Springer Science & Business Media
ISBN 13 : 1475728530
Total Pages : 269 pages
Book Rating : 4.4/5 (757 download)
Download or read book Multivariate Reduced-Rank Regression written by Raja Velu and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model.
Author : Pieter M. Kroonenberg
Publisher :
ISBN 13 : 9066950021
Total Pages : 434 pages
Book Rating : 4.0/5 (669 download)
Download or read book Three-mode Principal Component Analysis written by Pieter M. Kroonenberg and published by . This book was released on 1983 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Richard L. Gorsuch
Publisher : Routledge
ISBN 13 : 1317564898
Total Pages : 465 pages
Book Rating : 4.3/5 (175 download)
Download or read book Factor Analysis written by Richard L. Gorsuch and published by Routledge. This book was released on 2014-11-27 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use. This includes the theory as well as the empirical evaluations. The overall goal is to show readers how to use factor analysis in their substantive research by highlighting when the differences in mathematical procedures have a major impact on the substantive conclusions, when the differences are not relevant, and when factor analysis might not be the best procedure to use. Although the original version was written years ago, the book maintains its relevance today by providing readers with a thorough understanding of the basic mathematical models so they can easily apply these models to their own research. Readers are presented with a very complete picture of the "inner workings" of these methods. The new Introduction highlights the remarkably few changes that the author would make if he were writing the book today. An ideal text for courses on factor analysis or as a supplement for multivariate analysis, structural equation modeling, or advanced quantitative techniques taught in psychology, education, and other social and behavioral sciences, researchers who use these techniques also appreciate this book’s thorough review of the basic models. Prerequisites include a graduate level course on statistics and a basic understanding of algebra. Sections with an asterisk can be skipped entirely if preferred.
Author : Raphael Mrode
Publisher : CABI
ISBN 13 : 1800620489
Total Pages : 409 pages
Book Rating : 4.8/5 (6 download)
Download or read book Linear Models for the Prediction of the Genetic Merit of Animals, 4th Edition written by Raphael Mrode and published by CABI. This book was released on 2023-10-09 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamental to any livestock improvement programme by animal scientists, is the prediction of genetic merit in the offspring generation for desirable production traits such as increased growth rate, or superior meat, milk and wool production. Covering the foundational principles on the application of linear models for the prediction of genetic merit in livestock, this new edition is fully updated to incorporate recent advances in genomic prediction approaches, genomic models for multi-breed and crossbred performance, dominance and epistasis. It provides models for the analysis of main production traits as well as functional traits and includes numerous worked examples. For the first time, R codes for key examples in the textbook are provided online. Suitable for graduate and postgraduate students, researchers and lecturers of animal breeding, genetics and genomics, this established textbook provides a thorough grounding in both the basics and in new developments of linear models and animal genetics.
Author :
Publisher :
ISBN 13 :
Total Pages : 562 pages
Book Rating : 4.:/5 (89 download)
Download or read book U.S.D.A. Forest Service Research Paper NC. written by and published by . This book was released on 1968 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jae-On Kim
Publisher : SAGE
ISBN 13 : 9780803911659
Total Pages : 84 pages
Book Rating : 4.9/5 (116 download)
Download or read book Introduction to Factor Analysis written by Jae-On Kim and published by SAGE. This book was released on 1978-11 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes the mathematical and logical foundations at a level that does not presume advanced mathematical or statistical skills. It illustrates how to do factor analysis with several of the more popular packaged computer programs.
Author : Donal Stephen Jones
Publisher :
ISBN 13 :
Total Pages : 118 pages
Book Rating : 4.:/5 (29 download)
Download or read book An Empirical Investigation of Canonical Factor Analysis written by Donal Stephen Jones and published by . This book was released on 1961 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : W. Holmes Finch
Publisher : SAGE Publications
ISBN 13 : 1544339860
Total Pages : 92 pages
Book Rating : 4.5/5 (443 download)
Download or read book Exploratory Factor Analysis written by W. Holmes Finch and published by SAGE Publications. This book was released on 2019-09-05 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data. It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.
Author : Raymond Cattell
Publisher : Springer Science & Business Media
ISBN 13 : 1468422626
Total Pages : 635 pages
Book Rating : 4.4/5 (684 download)
Download or read book The Scientific Use of Factor Analysis in Behavioral and Life Sciences written by Raymond Cattell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John C. Loehlin
Publisher : Psychology Press
ISBN 13 : 1135614342
Total Pages : 303 pages
Book Rating : 4.1/5 (356 download)
Download or read book Latent Variable Models written by John C. Loehlin and published by Psychology Press. This book was released on 2004-05-20 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx. New in the fourth edition of Latent Variable Models: *a data CD that features the correlation and covariance matrices used in the exercises; *new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and *reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching. Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.
Author : Akinori Okada
Publisher : Springer Nature
ISBN 13 : 9819922402
Total Pages : 335 pages
Book Rating : 4.8/5 (199 download)
Download or read book Facets of Behaviormetrics written by Akinori Okada and published by Springer Nature. This book was released on 2023-09-17 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book is the first one written in English that deals comprehensively with behavior metrics. The term “behaviormetrics” comprehends the research including all sorts of quantitative approaches to disclose human behavior. Researchers in behavior metrics have developed, extended, and improved methods such as multivariate statistical analysis, survey methods, cluster analysis, machine learning, multidimensional scaling, corresponding analysis or quantification theory, network analysis, clustering, factor analysis, test theory, and related factors. In the spirit of behavior metrics, researchers applied these methods to data obtained by surveys, experiments, or websites from a diverse range of fields. The purpose of this book is twofold. One is to represent studies that display how the basic elements of behavior metrics have developed into present-day behavior metrics. The other is to represent studies performed mainly by those who would like to pioneer new fields of behavior metrics and studies that display elements of future behavior metrics. These studies consist of various characteristics such as those dealing with theoretical or conceptual subjects, the algorithm, the model, the method, and the application to a wide variety of fields. This book helps readers to understand the present and future of behavior metrics.
Author : Alexander T. Basilevsky
Publisher : John Wiley & Sons
ISBN 13 : 0470317736
Total Pages : 770 pages
Book Rating : 4.4/5 (73 download)
Download or read book Statistical Factor Analysis and Related Methods written by Alexander T. Basilevsky and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas: * The classical principal components model and sample-populationinference * Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain * Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores * The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable * Applications of factor models to the estimation of functionalforms and to least squares of regression estimators
Author : Rudolph J. Rummel
Publisher :
ISBN 13 :
Total Pages : 660 pages
Book Rating : 4.:/5 (321 download)
Download or read book Applied Factor Analysis written by Rudolph J. Rummel and published by . This book was released on 1970 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gregory C. Reinsel
Publisher : Springer Nature
ISBN 13 : 1071627937
Total Pages : 420 pages
Book Rating : 4.0/5 (716 download)
Download or read book Multivariate Reduced-Rank Regression written by Gregory C. Reinsel and published by Springer Nature. This book was released on 2022-11-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an account of multivariate reduced-rank regression, a tool of multivariate analysis that enjoys a broad array of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods, such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models, is also discussed. This new edition incorporates Big Data methodology and its applications, as well as high-dimensional reduced-rank regression, generalized reduced-rank regression with complex data, and sparse and low-rank regression methods. Each chapter contains developments of basic theoretical results, as well as details on computational procedures, illustrated with numerical examples drawn from disciplines such as biochemistry, genetics, marketing, and finance. This book is designed for advanced students, practitioners, and researchers, who may deal with moderate and high-dimensional multivariate data. Because regression is one of the most popular statistical methods, the multivariate regression analysis tools described should provide a natural way of looking at large (both cross-sectional and chronological) data sets. This book can be assigned in seminar-type courses taken by advanced graduate students in statistics, machine learning, econometrics, business, and engineering.
