Structural Equation Modeling With Lisrel Prelis And Simplis
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Structural Equation Modeling With Lisrel, Prelis, and Simplis by Barbara M. Byrne Pdf
This book illustrates the ease with which various features of LISREL 8 and PRELIS 2 can be implemented in addressing research questions that lend themselves to SEM. Its purpose is threefold: (a) to present a nonmathmatical introduction to basic concepts associated with SEM, (b) to demonstrate basic applications of SEM using both the DOS and Windows versions of LISREL 8, as well as both the LISREL and SIMPLIS lexicons, and (c) to highlight particular features of the LISREL 8 and PRELIS 2 progams that address important caveats related to SEM analyses. This book is intended neither as a text on the topic of SEM, nor as a comprehensive review of the many statistical funcitons available in the LISREL 8 and PRELIS 2 programs. Rather, the intent is to provide a practical guide to SEM using the LISREL approach. As such, the reader is "walked through" a diversity of SEM applications that include both factor analytic and full latent variable models, as well as a variety of data management procedures.
Interactive LISREL in Practice by Armando Luis Vieira Pdf
“Getting Started with a SIMPLIS Approach” is particularly appropriate for those users who are not experts in statistics, but have a basic understanding of multivariate analysis that would allow them to use this handbook as a good first foray into LISREL. Part I introduces the topic, presents the study that serves as the background for the explanation of matters, and provides the basis for Parts II and III, which, in turn, explain the process of estimation of the measurement model and the structural model, respectively. In each section, we also suggest essential literature to support the utilization of the handbook. After having read the book, readers will have acquired a basic knowledge of structural equation modeling, namely using the LISREL program, and will be prepared to continue with the learning process.
A Beginner's Guide to Structural Equation Modeling by Randall E. Schumacker,Richard G. Lomax Pdf
This best-seller introduces readers to structural equation modeling (SEM) so they can conduct their own analysis and critique related research. Noted for its accessible, applied approach, chapters cover basic concepts and practices and computer input/output from the free student version of Lisrel 8.8 in the examples. Each chapter features an outline, key concepts, a summary, numerous examples from a variety of disciplines, tables, and figures, including path diagrams, to assist with conceptual understanding. The book first reviews the basics of SEM, data entry/editing, and correlation. Next the authors highlight the basic steps of SEM: model specification, identification, estimation, testing, and modification, followed by issues related to model fit and power and sample size. Chapters 6 through 10 follow the steps of modeling using regression, path, confirmatory factor, and structural equation models. Next readers find a chapter on reporting SEM research including a checklist to guide decision-making, followed by one on model validation. Chapters 13 through 16 provide examples of various SEM model applications. The book concludes with the matrix approach to SEM using examples from previous chapters. Highlights of the new edition include: A website with raw data sets for the book's examples and exercises so they can be used with any SEM program, all of the book's exercises, hotlinks to related websites, and answers to all of the exercises for Instructor’s only New troubleshooting tips on how to address the most frequently encountered problems Examples now reference the free student version of Lisrel 8.8 Expanded coverage of advanced models with more on multiple-group, multi-level, & mixture modeling (Chs. 13 & 15), second-order and dynamic factor models (Ch. 14), and Monte Carlo methods (Ch. 16) Increased coverage of sample size and power (Ch. 5) and reporting research (Ch. 11) New journal article references help readers better understand published research (Chs. 13 – 17) and 25 % new exercises with answers to half in the book for student review. Designed for introductory graduate level courses in structural equation modeling or factor analysis taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. An understanding of correlation is assumed. To access the website visit the book page or the Textbook Resource page at http://www.psypress.com/textbook-resources/ for more details.
Basic Principles of Structural Equation Modeling by Ralph O. Mueller Pdf
During the last two decades, structural equation modeling (SEM) has emerged as a powerful multivariate data analysis tool in social science research settings, especially in the fields of sociology, psychology, and education. Although its roots can be traced back to the first half of this century, when Spearman (1904) developed factor analysis and Wright (1934) introduced path analysis, it was not until the 1970s that the works by Karl Joreskog and his associates (e. g. , Joreskog, 1977; Joreskog and Van Thillo, 1973) began to make general SEM techniques accessible to the social and behavioral science research communities. Today, with the development and increasing avail ability of SEM computer programs, SEM has become a well-established and respected data analysis method, incorporating many of the traditional analysis techniques as special cases. State-of-the-art SEM software packages such as LISREL (Joreskog and Sorbom, 1993a,b) and EQS (Bentler, 1993; Bentler and Wu, 1993) handle a variety of ordinary least squares regression designs as well as complex structural equation models involving variables with arbitrary distributions. Unfortunately, many students and researchers hesitate to use SEM methods, perhaps due to the somewhat complex underlying statistical repre sentation and theory. In my opinion, social science students and researchers can benefit greatly from acquiring knowledge and skills in SEM since the methods-applied appropriately-can provide a bridge between the theo retical and empirical aspects of behavioral research.
A Beginner's Guide to Structural Equation Modeling by Randall E. Schumacker,Richard G. Lomax Pdf
The second edition features: a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues. The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.
Applied Quantitative Analysis in Education and the Social Sciences by Yaacov Petscher,Christopher Schatschneider,Donald L. Compton Pdf
To say that complex data analyses are ubiquitous in the education and social sciences might be an understatement. Funding agencies and peer-review journals alike require that researchers use the most appropriate models and methods for explaining phenomena. Univariate and multivariate data structures often require the application of more rigorous methods than basic correlational or analysis of variance models. Additionally, though a vast set of resources may exist on how to run analysis, difficulties may be encountered when explicit direction is not provided as to how one should run a model and interpret results. The mission of this book is to expose the reader to advanced quantitative methods as it pertains to individual level analysis, multilevel analysis, item-level analysis, and covariance structure analysis. Each chapter is self-contained and follows a common format so that readers can run the analysis and correctly interpret the output for reporting.
Encyclopedia of Research Design by Neil J. Salkind Pdf
To request a free 30-day online trial to this product, visit www.sagepub.com/freetrial Research design can be daunting for all types of researchers. At its heart it might be described as a formalized approach toward problem solving, thinking, and acquiring knowledge—the success of which depends upon clearly defined objectives and appropriate choice of statistical tools, tests, and analysis to meet a project′s objectives. Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. Key Features Covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research Addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences Provides summaries of advantages and disadvantages of often-used strategies Uses hundreds of sample tables, figures, and equations based on real-life cases Key Themes Descriptive Statistics Distributions Graphical Displays of Data Hypothesis Testing Important Publications Inferential Statistics Item Response Theory Mathematical Concepts Measurement Concepts Organizations Publishing Qualitative Research Reliability of Scores Research Design Concepts Research Designs Research Ethics Research Process Research Validity Issues Sampling Scaling Software Applications Statistical Assumptions Statistical Concepts Statistical Procedures Statistical Tests Theories, Laws, and Principles Types of Variables Validity of Scores The Encyclopedia of Research Design is the perfect instrument for new learners as well as experienced researchers to explore both the original and newest branches of the field.
Structural Equation Modeling by Gregory R. Hancock,Ralph O. Mueller Pdf
Sponsored by the American Educational Research Association's Special Interest Group for Educational Statisticians This volume is the second edition of Hancock and Mueller’s highly-successful 2006 volume, with all of the original chapters updated as well as four new chapters. The second edition, like the first, is intended to serve as a didactically-oriented resource for graduate students and research professionals, covering a broad range of advanced topics often not discussed in introductory courses on structural equation modeling (SEM). Such topics are important in furthering the understanding of foundations and assumptions underlying SEM as well as in exploring SEM, as a potential tool to address new types of research questions that might not have arisen during a first course. Chapters focus on the clear explanation and application of topics, rather than on analytical derivations, and contain materials from popular SEM software.
Handbook of Quantitative Methods for Educational Research by Timothy Teo Pdf
As part of their research activities, researchers in all areas of education develop measuring instruments, design and conduct experiments and surveys, and analyze data resulting from these activities. Educational research has a strong tradition of employing state-of-the-art statistical and psychometric (psychological measurement) techniques. Commonly referred to as quantitative methods, these techniques cover a range of statistical tests and tools. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon of interest. Over the years, many methods and models have been developed to address the increasingly complex issues that educational researchers seek to address. This handbook serves to act as a reference for educational researchers and practitioners who desire to acquire knowledge and skills in quantitative methods for data analysis or to obtain deeper insights from published works. Written by experienced researchers and educators, each chapter in this handbook covers a methodological topic with attention paid to the theory, procedures, and the challenges on the use of that particular methodology. It is hoped that readers will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.
Handbook of Structural Equation Modeling by Rick H. Hoyle Pdf
"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--
Methodological Issues in Management Research by Rabi N. Subudhi,Sumita Mishra Pdf
Using contemporary examples of business and management research, predominantly within the context of India, this book offers numerous tools and techniques which can be applied to a diverse range of research needs. Topics discussed include: research designs, sampling, interviews, focus groups, case study research and mixed method research.
The Reviewer’s Guide to Quantitative Methods in the Social Sciences by Gregory R. Hancock,Laura M. Stapleton,Ralph O. Mueller Pdf
The Reviewer’s Guide to Quantitative Methods in the Social Sciences provides evaluators of research manuscripts and proposals in the social and behavioral sciences with the resources they need to read, understand, and assess quantitative work. 35 uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The second edition of this valuable resource updates readers on each technique’s key principles, appropriate usage, underlying assumptions and limitations, providing reviewers with the information they need to offer constructive commentary on works they evaluate. Written by methodological and applied scholars, this volume is also an indispensable author’s reference for preparing sound research manuscripts and proposals.
Structural Equation Modeling for Health and Medicine by Douglas D. Gunzler,Adam T. Perzynski,Adam C. Carle Pdf
Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also discuss techniques, such as mixture modeling, that expand the capacity of SEM using a combination of both continuous and categorical latent variables. Features: Basic, intermediate, and advanced SEM topics Detailed applications, particularly relevant for health and medical scientists Topics and examples that are pertinent to both new and experienced SEM researchers Substantive issues in health and medicine in the context of SEM Both methodological and applied examples Numerous figures and diagrams to illustrate the examples As SEM experts situated among clinicians and multidisciplinary researchers in medical settings, the authors provide a broad, current, on the ground understanding of the issues faced by clinical and health services researchers and decision scientists. This book gives health and medical researchers the tools to apply SEM approaches to study complex relationships between clinical measurements, individual and community-level characteristics, and patient-reported scales.
Application of Structural Equation Modeling in Educational Research and Practice by Myint Swe Khine Pdf
Structural Equation Modeling (SEM) is a statistical approach to testing hypothesis about the relationships among observed and latent variables. The use of SEM in research has increased in psychology, sociology, and economics in recent years. In particular educational researchers try to obtain the complete image of the process of education through the measurement of personality differences, learning environment, motivation levels and host of other variables that affect the teaching and learning process. With the use of survey instruments and interviews with students, teachers and other stakeholders as a lens, educators can assess and gain valuable information about the social ecology of the classrooms that could help in improving the instructional approach, classroom management and the learning organizations. A considerable number of research have been conducted to identify the factors and interactions between students’ characteristics, personal preferences, affective traits, study skills, and various other factors that could help in better educational performance. In recent years, educational researchers use Structural Equation Modeling (SEM) as a statistical technique to explore the complex and dynamic nature of interactions in educational research and practice. SEM is becoming a powerful analytical tool and making methodological advances in multivariate analysis. This book presents the collective works on concepts, methodologies and applications of SEM in educational research and practice. The anthology of current research described in this book will be a valuable resource for the next generation educational practitioners.
