A Step By Step Approach To Using The Sas System For Factor Analysis And Structural Equation Modeling
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A Step By Step Approach To Using The Sas System For Factor Analysis And Structural Equation Modeling
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Author : Larry Hatcher
language : en
Publisher: SAS Press
Release Date : 1994
A Step By Step Approach To Using The Sas System For Factor Analysis And Structural Equation Modeling written by Larry Hatcher and has been published by SAS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Using easy-to-comprehend terms and uncomplicated examples, author Larry Hatcher walks you, step-by-step, through this introduction to using SAS software for performing advanced statistical procedures in social science research and interpreting the results. Part one of the book discusses exploratory factor analysis at an easily understood, introductory level. Part two instructs the reader on how to use the CALIS procedure to perform confirmatory factor analysis, path analysis with manifest variables, and path analysis with latent variables. This book includes appendices that give basic instruction in using SAS software.
Applied Multivariate Analysis
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Author : Neil H. Timm
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-21
Applied Multivariate Analysis written by Neil H. Timm and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-21 with Mathematics categories.
Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.
A Step By Step Approach To Using Sas For Factor Analysis And Structural Equation Modeling
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Author : Larry Hatcher
language : en
Publisher: SAS Institute
Release Date : 2013-03-01
A Step By Step Approach To Using Sas For Factor Analysis And Structural Equation Modeling written by Larry Hatcher and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-01 with Computers categories.
Annotation Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all userseven those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.
Best Practices In Quantitative Methods
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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2008
Best Practices In Quantitative Methods written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language Arts & Disciplines categories.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Factor Analysis And Dimension Reduction In R
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Author : G. David Garson
language : en
Publisher: Taylor & Francis
Release Date : 2022-12-16
Factor Analysis And Dimension Reduction In R written by G. David Garson and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-16 with Psychology categories.
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.
Structural Equation Modeling
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Author : Jichuan Wang
language : en
Publisher: John Wiley & Sons
Release Date : 2019-12-04
Structural Equation Modeling written by Jichuan Wang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-04 with Mathematics categories.
Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspects of Structural Equation Modeling (SEM), this book demonstrates basic concepts and examples of various SEM models, along with updates on many advanced methods, including confirmatory factor analysis (CFA) with categorical items, bifactor model, Bayesian CFA model, item response theory (IRT) model, graded response model (GRM), multiple imputation (MI) of missing values, plausible values of latent variables, moderated mediation model, Bayesian SEM, latent growth modeling (LGM) with individually varying times of observations, dynamic structural equation modeling (DSEM), residual dynamic structural equation modeling (RDSEM), testing measurement invariance of instrument with categorical variables, longitudinal latent class analysis (LLCA), latent transition analysis (LTA), growth mixture modeling (GMM) with covariates and distal outcome, manual implementation of the BCH method and the three-step method for mixture modeling, Monte Carlo simulation power analysis for various SEM models, and estimate sample size for latent class analysis (LCA) model. The statistical modeling program Mplus Version 8.2 is featured with all models updated. It provides researchers with a flexible tool that allows them to analyze data with an easy-to-use interface and graphical displays of data and analysis results. Intended as both a teaching resource and a reference guide, and written in non-mathematical terms, Structural Equation Modeling: Applications Using Mplus, 2nd edition provides step-by-step instructions of model specification, estimation, evaluation, and modification. Chapters cover: Confirmatory Factor Analysis (CFA); Structural Equation Models (SEM); SEM for Longitudinal Data; Multi-Group Models; Mixture Models; and Power Analysis and Sample Size Estimate for SEM. Presents a useful reference guide for applications of SEM while systematically demonstrating various advanced SEM models Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes Provides step-by-step instructions of model specification and estimation, as well as detailed interpretation of Mplus results using real data sets Introduces different methods for sample size estimate and statistical power analysis for SEM Structural Equation Modeling is an excellent book for researchers and graduate students of SEM who want to understand the theory and learn how to build their own SEM models using Mplus.
E Business Models Services And Communications
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Author : Lee, In
language : en
Publisher: IGI Global
Release Date : 2007-11-30
E Business Models Services And Communications written by Lee, In and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-30 with Political Science categories.
With the rapid advancement in information technologies, e-business is rapidly growing in significance and is having a direct impact upon business applications and technologies. E-Business Models, Services and Communications provides researchers and practitioners with valuable information on recent advances and developments in emerging e-business models and technologies. This book covers a variety of topics such as e-business models, telecommunication network utilization, online consumer behavior, electronic communication adoption and service provider strategies, and privacy policies and implementation issues.
Research Methods And Design In Sport Management
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Author : Damon P. S. Andrew
language : en
Publisher: Human Kinetics
Release Date : 2011
Research Methods And Design In Sport Management written by Damon P. S. Andrew and has been published by Human Kinetics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
This text explains research design, implementation, analysis and assessment criteria with a focus on specific procedures unique to sport managament.
Planning For Information Systems
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Author : William R. King
language : en
Publisher: Routledge
Release Date : 2015-03-12
Planning For Information Systems written by William R. King and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-12 with Business & Economics categories.
Edited by one of the best-known and most widely respected figures in the field, "Planning for Information Systems" is a comprehensive, single source overview of the myriad ideas and processes that are identified with IS planning. While many chapters deal with high level strategic planning, the book gives equal attention to on-the-ground planning issues.Part I, 'Key Concepts of IS Planning', focuses on how IS planning has evolved over the years; business-IS strategic alignment; and the role of dynamic organizational capabilities in leveraging IS competencies. Part II, 'The Organizational IS Planning Process,' describes IS planning in terms of critical success factors and includes a knowledge-based view of IS planning; a practical assessment of strategic alignment; the IT budgeting process; the search for an optimal level of IS strategic planning; and the role of organizational learning in IS planning.Part III, 'IS Investment Planning', deals with predicting the value that an IS project may have; a 'rational expectations' approach to assessing project payoffs; assessing the social costs and benefits of projects; an options-based approach to managing project risks; planning for project teams; and the moderating effects of coordinated planning. Part IV, 'Goals and Outcomes of IS Planning', considers information strategy as a goal and/or outcome of IS planning; IT infrastructure as a goal or outcome; competitive advantage as a goal or outcome; e-process partnership chains; and planning successful Internet-based projects.
Linking Customer And Employee Satisfaction To The Bottom Line
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Author : Derek R. Allen
language : en
Publisher: Quality Press
Release Date : 2002-06-30
Linking Customer And Employee Satisfaction To The Bottom Line written by Derek R. Allen and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-06-30 with Business & Economics categories.
Most organizations recognize the impact that both customer and employee satisfaction have on overall financial performance. Actually acting on that information is the hard part. That is the focus of Linking Customer and Employee Satisfaction to the Bottom Line, which focuses on the relationship between customer satisfaction and tangible business outcomes like market share, revenue, and profitability. Intended for advanced service quality managers and marketing researchers with more than a modest exposure to statistical data analysis, this book provides a comprehensive overview of how these data may be related to critical business outcomes. Perhaps more importantly, researchers with mature customer satisfaction systems may use the techniques described in this book to maximize the value of their existing programs. While no technique or methodology can guarantee a strong link between customer satisfaction and key business outcomes, this book can ensure that appropriate scales, variables, and assumptions are used.