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Multiple Factor Analysis
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Book Synopsis Multiple Factor Analysis by Example Using R by : Jérôme Pagès
Download or read book Multiple Factor Analysis by Example Using R written by Jérôme Pagès and published by CRC Press. This book was released on 2014-11-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also inc
Book Synopsis Practical Guide To Principal Component Methods in R by : Alboukadel KASSAMBARA
Download or read book Practical Guide To Principal Component Methods in R written by Alboukadel KASSAMBARA and published by STHDA. This book was released on 2017-08-23 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.
Book Synopsis Multiple Correspondence Analysis and Related Methods by : Michael Greenacre
Download or read book Multiple Correspondence Analysis and Related Methods written by Michael Greenacre and published by CRC Press. This book was released on 2006-06-23 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su
Book Synopsis Making Sense of Factor Analysis by : Marjorie A. Pett
Download or read book Making Sense of Factor Analysis written by Marjorie A. Pett and published by SAGE. This book was released on 2003-03-21 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many health care practitioners and researchers are aware of the need to employ factor analysis in order to develop more sensitive instruments for data collection. Unfortunately, factor analysis is not a unidimensional approach that is easily understood by even the most experienced of researchers. Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research presents a straightforward explanation of the complex statistical procedures involved in factor analysis. Authors Marjorie A. Pett, Nancy M. Lackey, and John J. Sullivan provide a step-by-step approach to analyzing data using statistical computer packages like SPSS and SAS. Emphasizing the interrelationship between factor analysis and test construction, the authors examine numerous practical and theoretical decisions that must be made to efficiently run and accurately interpret the outcomes of these sophisticated computer programs. This accessible volume will help both novice and experienced health care professionals to Increase their knowledge of the use of factor analysis in health care research Understand journal articles that report the use of factor analysis in test construction and instrument development Create new data collection instruments Examine the reliability and structure of existing health care instruments Interpret and report computer-generated output from a factor analysis run Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research offers a practical method for developing tests, validating instruments, and reporting outcomes through the use of factor analysis. To facilitate learning, the authors provide concrete testing examples, three appendices of additional information, and a glossary of key terms. Ideal for graduate level nursing students, this book is also an invaluable resource for health care researchers.
Book Synopsis Factor Analysis by : Richard L. Gorsuch
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.
Book Synopsis Exploratory Multivariate Analysis by Example Using R by : Francois Husson
Download or read book Exploratory Multivariate Analysis by Example Using R written by Francois Husson and published by CRC Press. This book was released on 2017-04-25 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a
Book Synopsis Confirmatory Factor Analysis for Applied Research, Second Edition by : Timothy A. Brown
Download or read book Confirmatory Factor Analysis for Applied Research, Second Edition written by Timothy A. Brown and published by Guilford Publications. This book was released on 2015-01-07 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...
Book Synopsis Multiple-factor Analysis by : Louis Leon Thurstone
Download or read book Multiple-factor Analysis written by Louis Leon Thurstone and published by . This book was released on 1947 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Factor Analysis by : Jae-On Kim
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.
Book Synopsis Exploratory Factor Analysis by : W. Holmes Finch
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 133 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.
Book Synopsis Multiple-factor Analysis by : Louis Leon Thurstone
Download or read book Multiple-factor Analysis written by Louis Leon Thurstone and published by . This book was released on 1953 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Factor Analysis and Related Methods by : Roderick P. McDonald
Download or read book Factor Analysis and Related Methods written by Roderick P. McDonald and published by Psychology Press. This book was released on 1985 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1985. Routledge is an imprint of Taylor & Francis, an informa company.
Book Synopsis Computational Genomics with R by : Altuna Akalin
Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Book Synopsis Best Practices in Exploratory Factor Analysis by : Jason W. Osborne
Download or read book Best Practices in Exploratory Factor Analysis written by Jason W. Osborne and published by Createspace Independent Publishing Platform. This book was released on 2014-07-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Best Practices in Exploratory Factor Analysis (EFA) is a practitioner-oriented look at this popular and often-misunderstood statistical technique. We avoid formulas and matrix algebra, instead focusing on evidence-based best practices so you can focus on getting the most from your data.Each chapter reviews important concepts, uses real-world data to provide authentic examples of analyses, and provides guidance for interpreting the results of these analysis. Not only does this book clarify often-confusing issues like various extraction techniques, what rotation is really rotating, and how to use parallel analysis and MAP criteria to decide how many factors you have, but it also introduces replication statistics and bootstrap analysis so that you can better understand how precisely your data are helping you estimate population parameters. Bootstrap analysis also informs readers of your work as to the likelihood of replication, which can give you more credibility. At the end of each chapter, the author has recommendations as to how to enhance your mastery of the material, including access to the data sets used in the chapter through his web site. Other resources include syntax and macros for easily incorporating these progressive aspects of exploratory factor analysis into your practice. The web site will also include enrichment activities, answer keys to select exercises, and other resources. The fourth "best practices" book by the author, Best Practices in Exploratory Factor Analysis continues the tradition of clearly-written, accessible guides for those just learning quantitative methods or for those who have been researching for decades.NEW in August 2014! Chapters on factor scores, higher-order factor analysis, and reliability. Chapters: 1 INTRODUCTION TO EXPLORATORY FACTOR ANALYSIS 2 EXTRACTION AND ROTATION 3 SAMPLE SIZE MATTERS 4 REPLICATION STATISTICS IN EFA 5 BOOTSTRAP APPLICATIONS IN EFA 6 DATA CLEANING AND EFA 7 ARE FACTOR SCORES A GOOD IDEA? 8 HIGHER ORDER FACTORS 9 AFTER THE EFA: INTERNAL CONSISTENCY 10 SUMMARY AND CONCLUSIONS
Book Synopsis Factor Analysis at 100 by : Robert Cudeck
Download or read book Factor Analysis at 100 written by Robert Cudeck and published by Routledge. This book was released on 2007-03-06 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Foundations of Factor Analysis by : Stanley A Mulaik
Download or read book Foundations of Factor Analysis written by Stanley A Mulaik and published by CRC Press. This book was released on 2009-09-25 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited e
Book Synopsis Latent Structure Analysis by : Paul Felix Lazarsfeld
Download or read book Latent Structure Analysis written by Paul Felix Lazarsfeld and published by . This book was released on 1968 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
