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Multilevel Modeling of Social Problems
by Robert B. SmithUniquely focusing on intersections of social problems, multilevel statistical modeling, and causality; the substantively and methodologically integrated chapters of this book clarify basic strategies for developing and testing multilevel linear models (MLMs), and drawing casual inferences from such models. These models are also referred to as hierarchical linear models (HLMs) or mixed models. The statistical modeling of multilevel data structures enables researchers to combine contextual and longitudinal analyses appropriately. But researchers working on social problems seldom apply these methods, even though the topics they are studying and the empirical data call for their use. By applying multilevel modeling to hierarchical data structures, this book illustrates how the use of these methods can facilitate social problems research and the formulation of social policies. It gives the reader access to working data sets, computer code, and analytic techniques, while at the same time carefully discussing issues of causality in such models. This book innovatively: *Develops procedures for studying social, economic, and human development. * Uses typologies to group (i.e., classify or nest) the level of random macro-level factors. * Estimates models with Poisson, binomial, and Gaussian end points using SAS's generalized linear mixed models (GLIMMIX) procedure. * Selects appropriate covariance structures for generalized linear mixed models. * Applies difference-in-differences study designs in the multilevel modeling of intervention studies. *Calculates propensity scores by applying Firth logistic regression to Goldberger-corrected data. * Uses the Kenward-Rogers correction in mixed models of repeated measures. * Explicates differences between associational and causal analysis of multilevel models. * Consolidates research findings via meta-analysis and methodological critique. *Develops criteria for assessing a study's validity and zone of causality. Because of its social problems focus, clarity of exposition, and use of state-of-the-art procedures; policy researchers, methodologists, and applied statisticians in the social sciences (specifically, sociology, social psychology, political science, education, and public health) will find this book of great interest. It can be used as a primary text in courses on multilevel modeling or as a primer for more advanced texts.
Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R, & HLM™
by Professor George David GarsonMultilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLM™ provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson’s step-by-step instructions for the software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.
Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R, & HLM™
by Professor George David GarsonMultilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLM™ provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson’s step-by-step instructions for the software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.
Multilevel Modelling for Public Health and Health Services Research: Health in Context
by Alastair H. Leyland Peter P. GroenewegenThis open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download – not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets. The book’s practical review of MLA comprises: Theoretical, conceptual, and methodological backgroundStatistical backgroundThe modelling process and presentation of researchTutorials with example datasets Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis. “Leyland and Groenewegen’s wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis.” ̶ Juan Merlo, Professor of Social Epidemiology, Lund University “Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health”. ̶ S. (Subu) V. Subramanian, Professor of Population Health and Geography, Harvard University
Multilevel Statistical Models
by Harvey GoldsteinThroughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood. Multilevel modelling is now the accepted statistical technique for handling such data and is widely available in computer software packages. A thorough understanding of these techniques is therefore important for all those working in these areas. This new edition of Multilevel Statistical Models brings these techniques together, starting from basic ideas and illustrating how more complex models are derived. Bayesian methodology using MCMC has been extended along with new material on smoothing models, multivariate responses, missing data, latent normal transformations for discrete responses, structural equation modeling and survival models.Key Features:Provides a clear introduction and a comprehensive account of multilevel models.New methodological developments and applications are explored.Written by a leading expert in the field of multilevel methodology.Illustrated throughout with real-life examples, explaining theoretical concepts.This book is suitable as a comprehensive text for postgraduate courses, as well as a general reference guide. Applied statisticians in the social sciences, economics, biological and medical disciplines will find this book beneficial.
Multilevel Strategic Interaction Game Models for Complex Networks (Understanding Complex Systems Ser.)
by Francesco De Pellegrini Rachid El-Azouzi Konstantin Avrachenkov Eitan Altman Huijuan WangThis book provides a state-of-the-art overview on the dynamics and coevolution in multi-level strategic interaction games. As such it summarizes the results of the European CONGAS project, which developed new mathematical models and tools for the analysis, prediction and control of dynamical processes in systems possessing a rich multi-level structure and a web of interwoven interactions among elements with autonomous decision-making capabilities. The framework is built around game theoretical concepts, in particular evolutionary and multi-resolution games, and includes also techniques drawn from graph theory, statistical mechanics, control and optimization theory. Specific attention is devoted to systems that are prone to intermittency and catastrophic events due to the effect of collective dynamics.
Multilevel Structural Equation Modeling (Quantitative Applications in the Social Sciences #179)
by Levente Littvay Bruno Castanho Silva Constantin Manuel BosancianuMultilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Multilevel Structural Equation Modeling (Quantitative Applications in the Social Sciences #179)
by Levente Littvay Bruno Castanho Silva Constantin Manuel BosancianuMultilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Multilevel and Longitudinal Modeling with IBM SPSS (Quantitative Methodology Series)
by Ronald H. Heck Scott L. Thomas Lynn N. TabataMultilevel and Longitudinal Modeling with IBM SPSS, Third Edition, demonstrates how to use the multilevel and longitudinal modeling techniques available in IBM SPSS Versions 25-27. Annotated screenshots with all relevant output provide readers with a step-by-step understanding of each technique as they are shown how to navigate the program. Throughout, diagnostic tools, data management issues, and related graphics are introduced. SPSS commands show the flow of the menu structure and how to facilitate model building, while annotated syntax is also available for those who prefer this approach. Extended examples illustrating the logic of model development and evaluation are included throughout the book, demonstrating the context and rationale of the research questions and the steps around which the analyses are structured. The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques that facilitate working with multilevel, longitudinal, or cross-classified data sets. The next few chapters introduce the basics of multilevel modeling, developing a multilevel model, extensions of the basic two-level model (e.g., three-level models, models for binary and ordinal outcomes), and troubleshooting techniques for everyday-use programming and modeling problems along with potential solutions. Models for investigating individual and organizational change are next developed, followed by models with multivariate outcomes and, finally, models with cross-classified and multiple membership data structures. The book concludes with thoughts about ways to expand on the various multilevel and longitudinal modeling techniques introduced and issues (e.g., missing data, sample weights) to keep in mind in conducting multilevel analyses. Key features of the third edition: Thoroughly updated throughout to reflect IBM SPSS Versions 26-27. Introduction to fixed-effects regression for examining change over time where random-effects modeling may not be an optimal choice. Additional treatment of key topics specifically aligned with multilevel modeling (e.g., models with binary and ordinal outcomes). Expanded coverage of models with cross-classified and multiple membership data structures. Added discussion on model checking for improvement (e.g., examining residuals, locating outliers). Further discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures. Supported by online data sets, the book's practical approach makes it an essential text for graduate-level courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in departments of business, education, health, psychology, and sociology. The book will also prove appealing to researchers in these fields. The book is designed to provide an excellent supplement to Heck and Thomas's An Introduction to Multilevel Modeling Techniques, Fourth Edition; however, it can also be used with any multilevel or longitudinal modeling book or as a stand-alone text.
Multilevel and Longitudinal Modeling with IBM SPSS: Multilevel And Longitudinal Modeling With Ibm Spss (Quantitative Methodology Series)
by Ronald H. Heck Scott L. Thomas Lynn N. TabataThis book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED). Annotated screen shots provide readers with a step-by-step understanding of each technique and navigating the program. Readers learn how to set up, run, and interpret a variety of models. Diagnostic tools, data management issues, and related graphics are introduced throughout. Annotated syntax is also available for those who prefer this approach. Extended examples illustrate the logic of model development to show readers the rationale of the research questions and the steps around which the analyses are structured. The data used in the text and syntax examples are available at www.routledge.com/9780415817110. Highlights of the new edition include: Updated throughout to reflect IBM SPSS Version 21. Further coverage of growth trajectories, coding time-related variables, covariance structures, individual change and longitudinal experimental designs (Ch.5). Extended discussion of other types of research designs for examining change (e.g., regression discontinuity, quasi-experimental) over time (Ch.6). New examples specifying multiple latent constructs and parallel growth processes (Ch. 7). Discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures (Ch.1). The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques which facilitate working with multilevel, longitudinal, and cross-classified data sets. Chapters 3 and 4 introduce the basics of multilevel modeling: developing a multilevel model, interpreting output, and trouble-shooting common programming and modeling problems. Models for investigating individual and organizational change are presented in chapters 5 and 6, followed by models with multivariate outcomes in chapter 7. Chapter 8 provides an illustration of multilevel models with cross-classified data structures. The book concludes with ways to expand on the various multilevel and longitudinal modeling techniques and issues when conducting multilevel analyses. Ideal as a supplementary text for graduate courses on multilevel and longitudinal modeling, multivariate statistics, and research design taught in education, psychology, business, and sociology, this book’s practical approach also appeals to researchers in these fields. The book provides an excellent supplement to Heck & Thomas’s An Introduction to Multilevel Modeling Techniques, 2nd Edition; however, it can also be used with any multilevel and/or longitudinal modeling book or as a stand-alone text.
Multilinear Algebra (Algebra, Logic and Applications)
by Russell MerrisThe prototypical multilinear operation is multiplication. Indeed, every multilinear mapping can be factored through a tensor product. Apart from its intrinsic interest, the tensor product is of fundamental importance in a variety of disciplines, ranging from matrix inequalities and group representation theory, to the combinatorics of symmetric func
Multilinear Operator Integrals: Theory and Applications (Lecture Notes in Mathematics #2250)
by Anna Skripka Anna TomskovaThis book provides a comprehensive treatment of multilinear operator integral techniques. The exposition is structured to be suitable for a course on methods and applications of multilinear operator integrals and also as a research aid. The ideas and contributions to the field are surveyed and up-to-date results and methods are presented. Most practical constructions of multiple operator integrals are included along with fundamental technical results and major applications to smoothness properties of operator functions (Lipschitz and Hölder continuity, differentiability), approximation of operator functions, spectral shift functions, spectral flow in the setting of noncommutative geometry, quantum differentiability, and differentiability of noncommutative L^p-norms. Main ideas are demonstrated in simpler cases, while more involved, technical proofs are outlined and supplemented with references. Selected open problems in the field are also presented.
Multilingual Education Yearbook 2021: Policy and Practice in STEM Multilingual Contexts (Multilingual Education Yearbook)
by Anthony A. Essien Audrey MsimangaThis edited book attempts to foreground how challenges and complexities between policy and practice intertwine in the teaching and learning of the STEM subjects in multilingual settings, and how they (policy and practice) impact on educational processes, developments and outcomes. The unique feature of this book, thus, lies in its combination of not just language issues in the teaching and learning of the STEM subjects, but also in how these issues relate to policy and practice in multilingual contexts and how STEM research and practice may inform and shape language policies and their implementation in multilingual contexts. This book is of interest to stakeholders involved in STEM education such as researchers, undergraduate and graduate students, tertiary level teachers, teacher educators, curriculum developers as well as other professionals with responsibilities in STEM education subjects. The book is written in a way that is accessible to a wide range of backgrounds, including those who are in language education.
Multilingual Entity Linking (Synthesis Lectures on Human Language Technologies)
by Dan Roth Chen-Tse Tsai Shyam UpadhyayThis book focuses on Entity Discovery and Linking (EDL), which is the problem of identifying concepts and entities, disambiguating them, and grounding them to one or more knowledge bases (KBs). The authors first provide background on the topic and emphasize why it is a crucial step toward understanding natural language text. As most of the content on the internet is not in English, the book also discusses cross-lingual EDL. The authors present the challenges associated with EDL problems and explain the existing solutions. The book covers the core challenges that apply to all EDL problems, as well as the additional challenges associated with cross-lingual EDL problems. The authors also survey relevant research papers, highlight recent trends, and identify areas for future research.
Multimedia Environmental Models: The Fugacity Approach
by Donald Mackay J. Mark ParnisMultimedia Environmental Models: The Fugacity Approach, Third Edition, takes a broad approach of viewing chemical behavior in the total biosphere of connected biotic and abiotic compartments. Chemicals are subject to the laws of "mass balance," a constraint that provides the opportunity to establish quantitative expressions for chemical fate that are central to chemical management and regulatory legislation. This book employs both the conventional concentration-based procedures and those based on application of the more elegant and powerful concept of fugacity to characterize equilibrium, steady-state distribution, and time-dependent transport between environmental phases such as air, water, and soil. Organic chemicals are emphasized because they are more easily generalized when assessing environmental behavior.Features Illustrates professional approaches to calculating the fate of chemicals in the environment Explicitly details all worked examples in an annotated step-by-step fashion Presents real-life freely downloadable models of use to government, industry, and private consulting professionals and students alike Clarifies symbols and notation
Multimedia Technologies in the Internet of Things Environment, Volume 2 (Studies in Big Data #93)
by Rohit Sharma Prasant Kumar Pattnaik Raghvendra KumarThis book proposes a comprehensive overview of the state-of-the-art research work on multimedia analysis in IoT applications. This is a second volume by editors which provides theoretical and practical approach in the area of multimedia and IOT applications and performance analysis. Further, multimedia communication, deep learning models to multimedia data, and the new (IOT) approaches are also covered. It addresses the complete functional framework in the area of multimedia data, IoT, and smart computing techniques. It bridges the gap between multimedia concepts and solutions by providing the current IOT frameworks, their applications in multimedia analysis, the strengths and limitations of the existing methods, and the future directions in multimedia IOT analytics.
Multimedia Technologies in the Internet of Things Environment, Volume 3 (Studies in Big Data #108)
by Rohit Sharma Prasant Kumar Pattnaik Raghvendra KumarThis book proposes a comprehensive overview of the state-of-the-art research work on multimedia analysis in IoT applications. This is a third volume by editors which provides theoretical and practical approach in the area of multimedia and IOT applications and performance analysis. Further, multimedia communication, deep learning models to multimedia data, and the new (IOT) approaches are also covered. It addresses the complete functional framework in the area of multimedia data, IoT, and smart computing techniques. It bridges the gap between multimedia concepts and solutions by providing the current IOT frameworks, their applications in multimedia analysis, the strengths and limitations of the existing methods, and the future directions in multimedia IOT analytics.
Multimedia, Communication and Computing Application: Proceedings of the 2014 International Conference on Multimedia, Communication and Computing Application (MCCA 2014), Xiamen, China, October 16-17, 2014
by Ally Leung2014 International Conference on Multimedia, Communication and Computing Application (MCCA2014), Xiamen, China, Oct 16-17, 2014, provided a forum for experts and scholars of excellence from all over the world to present their latest work in the area of multimedia, communication and computing applications. In recent years, the multimedia techno
Multimodal Generative AI
by Krishna Kant Singh Akansha SinghThis book stands at the forefront of AI research, offering a comprehensive examination of multimodal generative technologies. Readers are taken on a journey through the evolution of generative models, from early neural networks to contemporary marvels like GANs and VAEs, and their transformative application in synthesizing realistic images and videos. In parallel, the text delves into the intricacies of language models, with a particular on revolutionary transformer-based designs. A core highlight of this work is its detailed discourse on integrating visual and textual models, laying out state-of-the-art techniques for creating cohesive, multimodal AI systems. “Multimodal Generative AI” is more than a mere academic text; it’s a visionary piece that speculates on the future of AI, weaving through case studies in autonomous systems, content creation, and human-computer interaction. The book also fosters a dialogue on responsible innovation in this dynamic field. Tailored for postgraduates, researchers, and professionals, this book is a must-read for anyone vested in the future of AI. It empowers its readers with the knowledge to harness the potential of multimodal systems in solving complex problems, merging visual understanding with linguistic prowess. This book can be used as a reference for postgraduates and researchers in related areas.
Multimodal Texts in Disciplinary Education: A Comprehensive Framework
by Kristina Danielsson Staffan SelanderThis open access book provides an introduction to multimodality and the role of multimodal texts in today’s education. Presenting a comprehensive framework for analysing and working with multimodal texts in disciplinary education, it serves as a tool for researchers and teachers alike. The second part of the book focuses on sample analyses of a variety of educational texts for different age groups and from different disciplines, including games and online resources. The authors also comment on the specific challenges of each text, and how teachers can discuss such texts with their students to enhance both their understanding of the content and their multimodal literacy. The book is intended for researchers in fields like education and multimodal studies, and for teacher educators, regardless of school subject or age group. With the combined perspectives on text analysis and implications for education, the book addresses the needs of teachers who want to work with multimodal aspects of texts in education in informed ways, but lack the right tools for such work.
Multimodal and Tensor Data Analytics for Industrial Systems Improvement (Springer Optimization and Its Applications #211)
by Panos M. Pardalos Nathan Gaw Mostafa Reisi GahrooeiThis volume covers the latest methodologies for using multimodal data fusion and analytics across several applications. The curated content presents recent developments and challenges in multimodal data analytics and shines a light on a pathway toward new research developments. Chapters are composed by eminent researchers and practitioners who present their research results and ideas based on their expertise. As data collection instruments have improved in quality and quantity for many applications, there has been an unprecedented increase in the availability of data from multiple sources, known as modalities. Modalities express a large degree of heterogeneity in their form, scale, resolution, and accuracy. Determining how to optimally combine the data for prediction and characterization is becoming increasingly important. Several research studies have investigated integrating multimodality data and discussed the challenges and limitations of multimodal data fusion. This volume provides a topical overview of various methods in multimodal data fusion for industrial engineering and operations research applications, such as manufacturing and healthcare.Advancements in sensing technologies and the shift toward the Internet of Things (IoT) has transformed and will continue to transform data analytics by producing new requirements and more complex forms of data. The abundance of data creates an unprecedented opportunity to design more efficient systems and make near-optimal operational decisions. On the other hand, the structural complexity and heterogeneity of the generated data pose a significant challenge to extracting useful features and patterns for making use of the data and facilitating decision-making. Therefore, continual research is needed to develop new statistical and analytical methodologies that overcome these data challenges and turn them into opportunities.
Multiobjective Linear Programming
by Dinh The LucThis book introduces the reader to the field of multiobjective optimization through problems with simple structures, namely those in which the objective function and constraints are linear. Fundamental notions as well as state-of-the-art advances are presented in a comprehensive way and illustrated with the help of numerous examples. Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems. The book was motivated by the fact that the majority of the practical problems we encounter in management science, engineering or operations research involve conflicting criteria and therefore it is more convenient to formulate them as multicriteria optimization models, the solution concepts and methods of which cannot be treated using traditional mathematical programming approaches.
Multiobjective Optimization Algorithms for Bioinformatics
by Ujjwal Maulik Sanghamitra Bandyopadhyay Anirban Mukhopadhyay Sumanta RayThis book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.
Multiobjective Programming and Planning
by Jared L. CohonThis text takes a broad view of multiobjective programming, emphasizing the methods most useful for continuous problems. It reviews multiobjective programming methods in the context of public decision-making problems, developing each problem within a context that addresses practical aspects of planning issues. Topics include a review of linear programming, the formulation of the general multiobjective programming problem, classification of multiobjective programming methods, techniques for generating noninferior solutions, multiple-decision-making methods, multiobjective analysis of water resource problems, and multiobjective analysis of facility location problems. 1978 edition.
Multiparameter Eigenvalue Problems: Sturm-Liouville Theory
by F.V. Atkinson Angelo B. MingarelliOne of the masters in the differential equations community, the late F.V. Atkinson contributed seminal research to multiparameter spectral theory and Sturm-Liouville theory. His ideas and techniques have long inspired researchers and continue to stimulate discussion. With the help of co-author Angelo B. Mingarelli, Multiparameter Eigenvalue Problem