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.

Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl’s structural causal model), and composite SEM (partial least squares path modeling). With increased emphasis on freely available software tools such as the R lavaan package, the text uses data examples from multiple disciplines to provide a comprehensive understanding of all phases of SEM--what to know, best practices, and pitfalls to avoid. It includes exercises with answers, rules to remember, topic boxes, and a new self-test on significance testing, regression, and psychometrics. The companion website supplies helpful primers on these topics as well as data, syntax, and output for the book's examples, in files that can be opened with any basic text editor. New to This Edition *Chapters on composite SEM, also called partial least squares path modeling or variance-based SEM; conducting SEM analyses in small samples; and recent developments in mediation analysis. *Coverage of new reporting standards for SEM analyses; piecewise SEM, also called confirmatory path analysis; comparing alternative models fitted to the same data; and issues in multiple-group SEM. *Extended tutorials on techniques for dealing with missing data in SEM and instrumental variable methods to deal with confounding of target causal effects. Pedagogical Features *New self-test of knowledge about background topics (significance testing, regression, and psychometrics) with scoring key and online primers. *End-of-chapter suggestions for further reading and exercises with answers. *Troublesome examples from real data, with guidance for handling typical problems in analyses. *Topic boxes on special issues and boxed rules to remember. *Website promoting a learn-by-doing approach, including data, extensively annotated syntax, and output files for all the book’s detailed examples.

Modeling and Simulation of Computer Networks and Systems: Methodologies and Applications introduces you to a broad array of modeling and simulation issues related to computer networks and systems. It focuses on the theories, tools, applications and uses of modeling and simulation in order to effectively optimize networks. It describes methodologies for modeling and simulation of new generations of wireless and mobiles networks and cloud and grid computing systems. Drawing upon years of practical experience and using numerous examples and illustrative applications recognized experts in both academia and industry, discuss: - Important and emerging topics in computer networks and systems including but not limited to; modeling, simulation, analysis and security of wireless and mobiles networks especially as they relate to next generation wireless networks - Methodologies, strategies and tools, and strategies needed to build computer networks and systems modeling and simulation from the bottom up - Different network performance metrics including, mobility, congestion, quality of service, security and more... Modeling and Simulation of Computer Networks and Systems is a must have resource for network architects, engineers and researchers who want to gain insight into optimizing network performance through the use of modeling and simulation. - Discusses important and emerging topics in computer networks and Systems including but not limited to; modeling, simulation, analysis and security of wireless and mobiles networks especially as they relate to next generation wireless networks - Provides the necessary methodologies, strategies and tools needed to build computer networks and systems modeling and simulation from the bottom up - Includes comprehensive review and evaluation of simulation tools and methodologies and different network performance metrics including mobility, congestion, quality of service, security and more

Design of complex artifacts and systems requires the cooperation of multidisciplinary design teams using multiple sophisticated commercial and non-commercial engine- ing tools such as CAD tools, modeling, simulation and optimization software, en- neering databases, and knowledge-based systems. Individuals or individual groups of multidisciplinary design teams usually work in parallel and independently with various engineering tools, which are located on different sites, often for quite a long period of time. At any moment, individual members may be working on different versions of a design or viewing the design from various perspectives, at different levels of details. In order to meet these requirements, it is necessary to have efficient comput- supported collaborative design systems. These systems should not only automate in- vidual tasks, in the manner of traditional computer-aided engineering tools, but also enable individual members to share information, collaborate, and coordinate their activities within the context of a design project. Based on close international collaboration between the University of Technology of Compiègne in France and the Institute of Computing Technology of the Chinese Ac- emy of Sciences in the early 1990s, a series of international workshops on CSCW in Design started in 1996. In order to facilitate the organization of these workshops, an International Working Group on CSCW in Design (CSCWD) was established and an International Steering Committee was formed in 1998. The series was converted to int- national conferences in 2000 building on the success of the four previous workshops.

Many approaches to creating Software Product Lines have emerged that are based on Model-Driven Engineering. This book introduces both Software Product Lines and Model-Driven Engineering, which have separate success stories in industry, and focuses on the practical combination of them. It describes the challenges and benefits of merging these two software development trends and provides the reader with a novel approach and practical mechanisms to improve software development productivity. The book is aimed at engineers and students who wish to understand and apply software product lines and model-driven engineering in their activities today. The concepts and methods are illustrated with two product line examples: the classic smart-home systems and a collection manager information system.

Help close the STEM gap through theory and practical tools Containing all of the practical tools needed to put theory into practice, STEM for All by Leena Bakshi McLean provides a roadmap for teachers, instructional coaches, and leaders to better understand the challenges that create low engagement and scores in STEM subjects and implement exciting and culturally relevant teaching plans. This book covers a wealth of key topics surrounding the subject, including classroom culture, discourse, identity, and belonging, family and community participation, and justice-centered core learning. This book uses the Connect, Create, and Cultivate framework from STEM4Real, an organization that provides socially just and culturally relevant STEM teaching and standards-based learning strategies, combined with stories and case studies of real students throughout to provide context for key concepts. In this book, readers will learn about: Six pillars that can throw off the foundation of a classroom, including non-inclusive curriculum and lack of equal access Moments of triumph and resilience that can be used to navigate rocky and recalcitrant relationships Implicit and unconscious biases that can unravel our impact despite our best intentions STEM for All earns a well-deserved spot on the bookshelves of all educators motivated to close the STEM gap and better prepare their students for future college and career opportunities in math and science fields.

Increasing complexity and performance and reliability expectations make modeling of automotive system both more difficult and more urgent. Automotive control has slowly evolved from an add-on to classical engine and vehicle design to a key technology to enforce consumption, pollution and safety limits. Modeling, however, is still mainly based on classical methods, even though much progress has been done in the identification community to speed it up and improve it. This book, the product of a workshop of representatives of different communities, offers an insight on how to close the gap and exploit this progress for the next generations of vehicles.

NATO Advanced Institute Ottawa, Ontario/ Canada, July 26 - August 6, 1982

This book is focused on mathematical modelling of chemical kinetics. The authors present the classification of basic models of chemical kinetics, thermokinetics and macrokinetics, as well as their application for the most important chemical transformations, such as combustion and catalysis. Readers will find a detailed description and analysis of different mathematical instruments which can be applied for simulation of reaction dynamics.