Download or read book Structural Equation Modeling Using R SAS written by Ding-Geng Chen and published by . This book was released on 2023-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "There has been considerable attention to making the methodologies of structural equation modeling available to researchers, practitioners, and students along with commonly used software. Structural Equation Modelling Using R/SAS aims to bring it all together to provide a concise point-of-reference for the most commonly used structural equation modeling from the fundamental level to the advanced level. This book is intended to contribute to the rapid development in structural equation modeling and its applications to real-world data. Straightforward explanations of the statistical theory and models related to structural equation models are provided, using a compilation of a variety of publicly available data, to provide an illustration of data analytics in a step-by-step fashion using commonly used statistical software of R and SAS. This book is appropriate for anyone who is interested in learning and practicing structural equation modeling, especially in using R and SAS. It is useful for applied statisticians, data scientists and practitioners, applied statistical analysts and scientists in public health, and academic researchers and graduate students in statistics, whilst also being of use to R&D professionals/practitioners in industry and governmental agencies"--
Download or read book Structural Equation Modeling Using R SAS written by Ding-Geng Chen and published by CRC Press. This book was released on 2023-08-21 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been considerable attention to making the methodologies of structural equation modeling available to researchers, practitioners, and students along with commonly used software. Structural Equation Modelling Using R/SAS aims to bring it all together to provide a concise point-of-reference for the most commonly used structural equation modeling from the fundamental level to the advanced level. This book is intended to contribute to the rapid development in structural equation modeling and its applications to real-world data. Straightforward explanations of the statistical theory and models related to structural equation models are provided, using a compilation of a variety of publicly available data, to provide an illustration of data analytics in a step-by-step fashion using commonly used statistical software of R and SAS. This book is appropriate for anyone who is interested in learning and practicing structural equation modeling, especially in using R and SAS. It is useful for applied statisticians, data scientists and practitioners, applied statistical analysts and scientists in public health, and academic researchers and graduate students in statistics, whilst also being of use to R&D professionals/practitioners in industry and governmental agencies. Key Features: Extensive compilation of commonly used structural equation models and methods from fundamental to advanced levels Straightforward explanations of the theory related to the structural equation models Compilation of a variety of publicly available data Step-by-step illustrations of data analysis using commonly used statistical software R and SAS Data and computer programs are available for readers to replicate and implement the new methods to better understand the book contents and for future applications Handbook for applied statisticians and practitioners
Download or read book A Step by Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling Second Edition written by Norm O'Rourke, Ph.D., R.Psych. and published by SAS Institute. This book was released on 2013-03-23 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-understand guide makes SEM accessible to all users. 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.
Download or read book Multivariate Analysis with LISREL written by Karl G. Jöreskog and published by Springer. This book was released on 2016-10-17 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.
Download or read book A Step by Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling Second Edition 2nd Edition written by R. O'Rourke and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-understand guide makes SEM accessible to all users. 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.
Download or read book SAS and R written by Ken Kleinman and published by CRC Press. This book was released on 2009-07-21 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: An All-in-One Resource for Using SAS and R to Carry out Common TasksProvides a path between languages that is easier than reading complete documentationSAS and R: Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in both SAS and R, without having to navigate through the extensive, id
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.
Download or read book A Step by Step Approach to Using SAS for Univariate Multivariate Statistics written by Norm O'Rourke and published by SAS Institute. This book was released on 2005 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing practice data inspired by actual studies, this book explains how to choose the right statistic, understand the assumptions underlying the procedure, prepare an SAS program for an analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association.
Download or read book Structural Equation Modeling Using SAS written by Catherine Truxillo and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This course introduces the experienced statistical analyst to structural equation modeling (SEM) and the new PATH language in the CALIS procedure in SAS/STAT software. The course also introduces the SAS with an easy-to-use diagram-creating interface. Structural equation modeling is a statistical technique that combines elements of traditional multivariate models, such as regression analysis, factor analysis, and simultaneous equation modeling. These models are often represented as matrices, equations, and/or path diagrams and can explicitly account for uncertainty in observed variables and for estimation bias due to measurement error. Competing models can be compared to one another, providing information about the complex drivers of the outcome variables of interest. Many applications of SEM can be found in the social, economic, and behavioral sciences, where measurement error and uncertain causal conditions are commonly encountered." -- page [vi].
Download or read book Growth Modeling written by Kevin J. Grimm and published by Guilford Publications. This book was released on 2016-10-17 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.
Download or read book Advanced Regression Models with SAS and R written by Olga Korosteleva and published by CRC Press. This book was released on 2018-12-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book consists of regression models that go beyond linear regression, including models for right-skewed, categorical and hierarchical observations. The book presents the theory as well as fully worked-out numerical examples with complete SAS and R codes for each regression. The emphasis is on model accuracy and the interpretation of results. For each regression, the fitted model is presented along with interpretation of estimated regression coefficients and prediction of response for given values of predictors. Features: Presents the theoretical framework for each regression. Discusses data that are categorical, count, proportions, right-skewed, longitudinal and hierarchical. Uses examples based on real-life consulting projects. Provides complete SAS and R codes for each example. Includes several exercises for every regression. Advanced Regression Models with SAS and R is designed as a text for an upper division undergraduate or a graduate course in regression analysis. Prior exposure to the two software packages is desired but not required. The Author: Olga Korosteleva is a Professor of Statistics at California State University, Long Beach. She teaches a large variety of statistical courses to undergraduate and master’s students. She has published three statistical textbooks. For a number of years, she has held the position of faculty director of the statistical consulting group. Her research interests lie mostly in applications of statistical methodology through collaboration with her clients in health sciences, nursing, kinesiology, and other fields.
Download or read book SAS Structural Equation Modeling 2 for Jmp written by Sas Institute and published by SAS Institute. This book was released on 2014-05-14 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Documenting a graphical user interface that provides easy access to structural equation modeling techniques, this book enables you to quickly specify models in graphical form to represent the hypothesized relationships among the variables. It is accessed from the JMP application and uses the SAS/STAT CALIS procedure to perform computations.
Download or read book An R and S Plus Companion to Applied Regression written by John Fox and published by SAGE. This book was released on 2002-06-05 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville
Download or read book Basics of Structural Equation Modeling written by Geoffrey M. Maruyama and published by SAGE Publications. This book was released on 1997-09-22 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the availability of software programs such as LISREL, EQS, and AMOS modeling techniques have become a popular tool for formalized presentation of the hypothesized relationships underlying correlational research and for testing the plausibility of hypothesizing for a particular data set. The popularity of these techniques, however, has often led to misunderstandings of them, particularly by students being exposed to them for the first time. Through the use of careful narrative explanation, Basics of Structural Equation Modeling describes the logic underlying structural equation modeling (SEM) approaches, describes how SEM approaches relate to techniques like regression and factor analysis, analyzes the strengths and shortcomings of SEM as compared to alternative methodologies, and explores the various methodologies for analyzing structural equation data.
Download or read book Latent Growth Curve Modeling written by Kristopher J. Preacher and published by SAGE Publications. This book was released on 2008-06-27 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Latent growth curve modeling (LGM)—a special case of confirmatory factor analysis designed to model change over time—is an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit. The book covers the basic linear LGM, and builds from there to describe more complex functional forms (e.g., polynomial latent curves), multivariate latent growth curves used to model simultaneous change in multiple variables, the inclusion of time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models. The authors also highlight approaches to dealing with missing data, different estimation methods, and incorporate discussion of model evaluation and comparison within the context of LGM. The models demonstrate how they may be applied to longitudinal data derived from the NICHD Study of Early Child Care and Youth Development (SECCYD).. Key Features · Provides easy-to-follow, didactic examples of several common growth modeling approaches · Highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit · Explains the commonalities and differences between latent growth model and multilevel modeling of repeated measures data · Covers the basic linear latent growth model, and builds from there to describe more complex functional forms such as polynomial latent curves, multivariate latent growth curves, time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models
Download or read book A Handbook of Statistical Analyses Using R Second Edition written by Torsten Hothorn and published by CRC Press. This book was released on 2009-07-20 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.
Download or read book Structural Equation Modeling with SAS CALIS written by Jennifer Leah Hunter and published by . This book was released on 2005 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:
