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Book Structural Modeling by Example

Download or read book Structural Modeling by Example written by Peter Cuttance and published by Cambridge University Press. This book was released on 1987 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive overview of the application of structural equation models in the social and behavioural sciences and in educational research.

Book Structural Modeling and Analysis

Download or read book Structural Modeling and Analysis written by Clive L. Dym and published by Cambridge University Press. This book was released on 1997-06-13 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern, unified introduction to structural modelling and analysis, with an emphasis on the application of energy methods.

Book Longitudinal Structural Equation Modeling

Download or read book Longitudinal Structural Equation Modeling written by Todd D. Little and published by Guilford Publications. This book was released on 2023-12-27 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beloved for its engaging, conversational style, this valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book’s figures. New to This Edition: *Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux. *Chapter on longitudinal mixture modeling, with Whitney Moore. *Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne. *Chapter on Bayesian SEM, with Mauricio Garnier. *Revised throughout with new developments and discussions, such as how to test models of experimental effects.

Book Structural Modeling and Experimental Techniques  Second Edition

Download or read book Structural Modeling and Experimental Techniques Second Edition written by Harry G. Harris and published by CRC Press. This book was released on 1999-03-30 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Modeling and Experimental Techniques presents a current treatment of structural modeling for applications in design, research, education, and product development. Providing numerous case studies throughout, the book emphasizes modeling the behavior of reinforced and prestressed concrete and masonry structures. Structural Modeling and Experimental Techniques: Concentrates on the modeling of the true inelastic behavior of structures Provides case histories detailing applications of the modeling techniques to real structures Discusses the historical background of model analysis and similitude principles governing the design, testing, and interpretation of models Evaluates the limitations and benefits of elastic models Analyzes materials for reinforced concrete masonry and steel models Assesses the critical nature of scale effects of model testing Describes selected laboratory techniques and loading methods Contains material on errors as well as the accuracy and reliability of physical modeling Examines dynamic similitude and modeling techniques for studying dynamic loading of structures Covers actual applications of structural modeling This book serves students in model analysis and experimental methods, professionals manufacturing and testing structural models, as well as professionals testing large or full-scale structures - since the instrumentation techniques and overall approaches for testing large structures are very similar to those used in small-scale modeling work.

Book Structural Equations with Latent Variables

Download or read book Structural Equations with Latent Variables written by Kenneth A. Bollen and published by John Wiley & Sons. This book was released on 2014-08-28 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods and contains an integrated comparison of the available strategies for analyzing ordinal data. This is a case study work with illuminating examples taken from across the wide spectrum of ordinal categorical applications. 1984 (0 471-89055-3) 287 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch This book provides the practicing statistician and econometrician with new tools for assessing the quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are either unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data and help to identify the variables involved in each; and pinpoint the estimated coefficients that are potentially most adversely affected. The primary emphasis of these contributions is on diagnostics, but suggestions for remedial action are given and illustrated. 1980 (0 471-05856-4) 292 pp. Applied Regression Analysis Second Edition Norman Draper and Harry Smith Featuring a significant expansion of material reflecting recent advances, here is a complete and up-to-date introduction to the fundamentals of regression analysis, focusing on understanding the latest concepts and applications of these methods. The authors thoroughly explore the fitting and checking of both linear and nonlinear regression models, using small or large data sets and pocket or high-speed computing equipment. Features added to this Second Edition include the practical implications of linear regression; the Durbin-Watson test for serial correlation; families of transformations; inverse, ridge, latent root and robust regression; and nonlinear growth models. Includes many new exercises and worked examples. 1981 (0 471-02995-5) 709 pp.

Book Structural Modeling and Experimental Techniques  Second Edition

Download or read book Structural Modeling and Experimental Techniques Second Edition written by Harry G. Harris and published by CRC Press. This book was released on 1999-03-30 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Modeling and Experimental Techniques presents a current treatment of structural modeling for applications in design, research, education, and product development. Providing numerous case studies throughout, the book emphasizes modeling the behavior of reinforced and prestressed concrete and masonry structures. Structural Modeling and Experimental Techniques: Concentrates on the modeling of the true inelastic behavior of structures Provides case histories detailing applications of the modeling techniques to real structures Discusses the historical background of model analysis and similitude principles governing the design, testing, and interpretation of models Evaluates the limitations and benefits of elastic models Analyzes materials for reinforced concrete masonry and steel models Assesses the critical nature of scale effects of model testing Describes selected laboratory techniques and loading methods Contains material on errors as well as the accuracy and reliability of physical modeling Examines dynamic similitude and modeling techniques for studying dynamic loading of structures Covers actual applications of structural modeling This book serves students in model analysis and experimental methods, professionals manufacturing and testing structural models, as well as professionals testing large or full-scale structures - since the instrumentation techniques and overall approaches for testing large structures are very similar to those used in small-scale modeling work.

Book Structural Equation Modeling With AMOS

Download or read book Structural Equation Modeling With AMOS written by Barbara M. Byrne and published by Psychology Press. This book was released on 2001-04 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and appli.

Book Partial Least Squares Structural Equation Modeling  PLS SEM  Using R

Download or read book Partial Least Squares Structural Equation Modeling PLS SEM Using R written by Joseph F. Hair Jr. and published by Springer Nature. This book was released on 2021-11-03 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software’s SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the “how-tos” of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.

Book A Beginner s Guide to Structural Equation Modeling

Download or read book A Beginner s Guide to Structural Equation Modeling written by Randall E. Schumacker and published by Routledge. This book was released on 2010 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a basic introduction to structural equation modeling (SEM) and focuses on the conceptual steps to be taken in analysing conceptual models.

Book A Beginner s Guide to Structural Equation Modeling

Download or read book A Beginner s Guide to Structural Equation Modeling written by Randall E. Schumacker and published by Routledge. This book was released on 2015-12-22 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Noted for its crystal clear explanations, this book is considered the most comprehensive introductory text to structural equation modeling (SEM). Noted for its thorough review of basic concepts and a wide variety of models, this book better prepares readers to apply SEM to a variety of research questions. Programming details and the use of algebra are kept to a minimum to help readers easily grasp the concepts so they can conduct their own analysis and critique related research. Featuring a greater emphasis on statistical power and model validation than other texts, each chapter features key concepts, examples from various disciplines, tables and figures, a summary, and exercises. Highlights of the extensively revised 4th edition include: -Uses different SEM software (not just Lisrel) including Amos, EQS, LISREL, Mplus, and R to demonstrate applications. -Detailed introduction to the statistical methods related to SEM including correlation, regression, and factor analysis to maximize understanding (Chs. 1 – 6). -The 5 step approach to modeling data (specification, identification, estimation, testing, and modification) is now covered in more detail and prior to the modeling chapters to provide a more coherent view of how to create models and interpret results (ch. 7). -More discussion of hypothesis testing, power, sampling, effect sizes, and model fit, critical topics for beginning modelers (ch. 7). - Each model chapter now focuses on one technique to enhance understanding by providing more description, assumptions, and interpretation of results, and an exercise related to analysis and output (Chs. 8 -15). -The use of SPSS AMOS diagrams to describe the theoretical models. -The key features of each of the software packages (Ch. 1). -Guidelines for reporting SEM research (Ch. 16). -www.routledge.com/9781138811935 which provides access to data sets that can be used with any program, links to other SEM examples, related readings, and journal articles, and more. Reorganized, the new edition begins with a more detailed introduction to SEM including the various software packages available, followed by chapters on data entry and editing, and correlation which is critical to understanding how missing data, non-normality, measurement, and restriction of range in scores affects SEM analysis. Multiple regression, path, and factor models are then reviewed and exploratory and confirmatory factor analysis is introduced. These chapters demonstrate how observed variables share variance in defining a latent variables and introduce how measurement error can be removed from observed variables. Chapter 7 details the 5 SEM modeling steps including model specification, identification, estimation, testing, and modification along with a discussion of hypothesis testing and the related issues of power, and sample and effect sizes.Chapters 8 to 15 provide comprehensive introductions to different SEM models including Multiple Group, Second-Order CFA, Dynamic Factor, Multiple-Indicator Multiple-Cause, Mixed Variable and Mixture, Multi-Level, Latent Growth, and SEM Interaction Models. Each of the 5 SEM modeling steps is explained for each model along with an application. Chapter exercises provide practice with and enhance understanding of the analysis of each model. The book concludes with a review of SEM guidelines for reporting research. Designed for introductory graduate courses in structural equation modeling, factor analysis, advanced, multivariate, or applied statistics, quantitative techniques, or statistics II taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. Prerequisites include an introduction to intermediate statistics that covers correlation and regression principles.

Book Innovations in Multivariate Statistical Analysis

Download or read book Innovations in Multivariate Statistical Analysis written by Risto D.H. Heijmans and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three decades which have followed the publication of Heinz Neudecker's seminal paper `Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products' in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines. Amongst these are the disciplines to which Neudecker has contributed directly - namely econometrics, economics, psychometrics and multivariate analysis. This book aims to illustrate how powerful the tools of matrix analysis have become as weapons in the statistician's armoury. The majority of its chapters are concerned primarily with theoretical innovations, but all of them have applications in view, and some of them contain extensive illustrations of the applied techniques. This book will provide research workers and graduate students with a cross-section of innovative work in the fields of matrix methods and multivariate statistical analysis. It should be of interest to students and practitioners in a wide range of subjects which rely upon modern methods of statistical analysis. The contributors to the book are themselves practitioners of a wide range of subjects including econometrics, psychometrics, educational statistics, computation methods and electrical engineering, but they find a common ground in the methods which are represented in the book. It is envisaged that the book will serve as an important work of reference and as a source of inspiration for some years to come.

Book R for Data Science

    Book Details:
  • Author : Hadley Wickham
  • Publisher : "O'Reilly Media, Inc."
  • Release : 2016-12-12
  • ISBN : 1491910364
  • Pages : 521 pages

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Book Structural Equation Modeling

Download or read book Structural Equation Modeling written by Jichuan Wang and published by John Wiley & Sons. This book was released on 2019-12-04 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Structural Equation Modeling

Download or read book Structural Equation Modeling written by Natasha K. Bowen and published by Oxford University Press. This book was released on 2011-09-23 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural Equation Modeling (SEM) has long been used in social work research, but the writing on the topic is typically fragmented and highly technical. This pocket guide fills a major gap in the literature by providing social work researchers and doctoral students with an accessible synthesis. The authors demonstrate two SEM programs with distinct user interfaces and capabilities (Amos and Mplus) with enough specificity that readers can conduct their own analyses without consulting additional resources. Examples from social work literature highlight best practices for the specification, estimation, interpretation, and modification of structural equation models. Unlike most sources on SEM, this book provides clear guidelines on how to evaluate SEM output and how to proceed when model fit is not acceptable. Oftentimes, confirmatory factor analysis and general structure modeling are the most flexible, powerful, and appropriate choices for social work data. Richly illustrated with figures, equations, matrices, and tables, this pocket guide empowers social workers with a set of defensible analysis strategies that allows for competent, confident use of SEM.