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Middleware provides an integration framework for multiple and potentially - verse computing platforms. It allows developers to engineer distributed appli- tions more easily, providing abstractions and primitives to handle distribution and coordination. Middlewareisconstantlyfacingnewchallenges.Today&#8217;sadvancesincomp- ing, including development of pervasive applications, exacerbates the diversity problem, introducing variations not only in terms of performance, but also in terms of environments and device characteristics. Software engineers are the- fore challenged both in the area of the development of new and scalable m- dleware systems, where open, heterogeneous, component-based platforms should provide richer functionality and services, and in the area of application devel- ment, where tools to simplify the use of middleware solutions are necessary. Software Engineering and Middleware is the premier workshop for the - search and practice community of software engineering working in both areas to presentanddiscussnewideasinthis?eld.SEM2004wasthefourthinternational workshop on software engineering and middleware of the EDO/SEM workshop series. Previous workshops of this series were successfully held in 2002, 2000 and 1999. Most of the proceedings have been published by Springer in the Lecture Notes in Computer Science series.

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'Kline is a master at explaining complex concepts in a very accessible manner. It is refreshing to see a new edition of an important book that truly is new, not simply redesigned. The fourth edition successfully incorporates recent developments in SEM and contemporary forms of causal reasoning and analysis, such as the SCM. Unlike most SEM texts, this book is notable for making a sophisticated, often-difficult statistical technique understandable to non-statisticians without watering down the material. Kline makes excellent use of relevant statistical theory without overwhelming the reader with algebraic matrices, proofs, formulas, and statistical notations. I recommend this book without reservation to researchers, instructors, and students in the social and behavioral sciences. It is far more than an introduction to SEM--in my opinion, it is a potential catalyst for reconsidering the statistical methods that researchers apply to better understand human action and interaction.'--Chris L. S. Coryn, PhD, Director, Interdisciplinary PhD in Evaluation, Western Michigan University'Too often, new editions of statistics books do not have substantive changes, but that is not the case here--Kline has made significant improvements to an already excellent book. Staying current is particularly necessary in SEM, where the theory has been developing rapidly in the last 10 years, yielding, for example, better estimation methods for categorical data and Bayesian methods. Helpful features include the topic boxes, which allow detailed discussion of particular topics without interfering with the overall flow of the text. I also like the exercises at the end of each chapter, which highlight the important parts of the chapter and provide crucial learning opportunities. Kline&#8217;s use of the companion website to distribute real examples is excellent. After reading about the models and analyses, it is helpful--actually vital--to be able to practice running the models in various software packages.'--Craig S. Wells, PhD, Department of Educational Policy, Research, and Administration, University of Massachusetts Amherst'The best place to start for anyone who wants to learn the basics of SEM. The text emphasizes applied SEM content without relying on statistical formulas and the writing is clear and well organized, which is very helpful for students. I appreciate having exercises with answers that students can complete and check on their own. The examples are very helpful, and reflect the fact that real data are often troublesome. The website is easy to use and more extensive than for many other books.'--Donna Harrington, PhD, University of Maryland School of Social Work'The incorporation of Pearl&#8217;s approach to causal inference is a major improvement in the fourth edition. This is the most useful introductory SEM book out there. I have recommended this book to colleagues for both personal and class use, and will continue to do so.'--Richard K. Wagner, PhD, Distinguished Professor of Psychology, Florida State University; Associate Director, Florida Center for Reading Research'This book is unique in that it treats structural equation models for what they are--carriers of causal assumptions and tools for causal inference. Gone are the inhibitions and trepidation that characterize most SEM texts in their treatments of causal inference. Overall, the book elevates SEM education to a new level of modernity and promises to usher in a renaissance for a field that pioneered causal analysis in the behavioral sciences.'--Judea Pearl, PhD, Department of Computer Science, University of California, Los Angeles 'Perfectly addresses the needs of social scientists like me without formal training in mathematical statistics....Can be read by any graduate in psychology or even by keen undergraduates interested in exploring new vistas. Yet it will also constitute a surprisingly good read for experienced researchers in search of some refreshing insights in their favorite techniques....A real tour de force....Succeeds in reconciling comprehensiveness and comprehensibility.'--The Psychologist (on the second edition) 'The greatest strength of this book is Kline's ability to present materials in an engaging, accessible manner. In nearly all situations

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This student orientated guide to structural equation modeling promotes theoretical understanding and inspires students with the confidence to successfully apply SEM. Assuming no previous experience, and a minimum of mathematical knowledge, this is an invaluable companion for students taking introductory SEM courses in any discipline. Niels Blunch shines a light on each step of the structural equation modeling process, providing a detailed introduction to SPSS and EQS with a focus on EQS' excellent graphical interface. He also sets out best practice for data entry and programming, and uses real life data to show how SEM is applied in research. The book includes: Learning objectives, key concepts and questions for further discussion in each chapter. Helpful diagrams and screenshots to expand on concepts covered in the texts. A wide variety of examples from multiple disciplines and real world contexts. Exercises for each chapter on an accompanying . A detailed glossary. Clear, engaging and built around key software, this is an ideal introduction for anyone new to SEM.

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