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Handbook Of Structural Equation Modeling

Author: Rick H. Hoyle
Publisher: Guilford Publications
ISBN: 1462516793
Size: 67.74 MB
Format: PDF, Mobi
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The first comprehensive structural equation modeling (SEM) handbook, this accessible volume presents both the mechanics of SEM and specific SEM strategies and applications. The editor, 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.

Handbook Of Latent Variable And Related Models

Author:
Publisher: Elsevier
ISBN: 9780080471266
Size: 37.51 MB
Format: PDF, ePub, Docs
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This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables. - Covers a wide class of important models - Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data - Includes illustrative examples with real data sets from business, education, medicine, public health and sociology. - Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.

Principles And Practice Of Structural Equation Modeling Fourth Edition

Author: Rex B. Kline
Publisher: Guilford Publications
ISBN: 146252334X
Size: 50.57 MB
Format: PDF, ePub, Docs
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New to This Edition *Extensively revised to cover important new topics: Pearl' s graphing theory and SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. *Expanded coverage of psychometrics. *Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). *Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models. Pedagogical Features *Exercises with answers, plus end-of-chapter annotated lists of further reading. *Real examplesof troublesome data, demonstrating how to handle typical problems in analyses.

Structural Equation Modeling

Author: Sik-Yum Lee
Publisher: Wiley
ISBN: 9780470024232
Size: 41.10 MB
Format: PDF, ePub
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***Winner of the 2008 Ziegel Prize for outstanding new book of the year*** Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples. Structural Equation Modeling introduces the Bayesian approach to SEMs, including the selection of prior distributions and data augmentation, and offers an overview of the subject’s recent advances. Demonstrates how to utilize powerful statistical computing tools, including the Gibbs sampler, the Metropolis-Hasting algorithm, bridge sampling and path sampling to obtain the Bayesian results. Discusses the Bayes factor and Deviance Information Criterion (DIC) for model comparison. Includes coverage of complex models, including SEMs with ordered categorical variables, and dichotomous variables, nonlinear SEMs, two-level SEMs, multisample SEMs, mixtures of SEMs, SEMs with missing data, SEMs with variables from an exponential family of distributions, and some of their combinations. Illustrates the methodology through simulation studies and examples with real data from business management, education, psychology, public health and sociology. Demonstrates the application of the freely available software WinBUGS via a supplementary website featuring computer code and data sets. Structural Equation Modeling: A Bayesian Approach is a multi-disciplinary text ideal for researchers and students in many areas, including: statistics, biostatistics, business, education, medicine, psychology, public health and social science.

Handbook Of Psychology Research Methods In Psychology

Author: Irving B. Weiner
Publisher: John Wiley & Sons
ISBN: 9780471385134
Size: 72.87 MB
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This book provides a comprehensive overview of methods of data collection and analysis in psychological science. Chapter address basic considerations in research design-such as formulating hypothesis, selecting participant samples, identifying independent and dependent variables, and determining appropriate procedures-and alternative techniques for statistical treatment of data, such as categorical and factorial methods, path analysis and logistic regression, and meta-analysis.

Ecological Statistics

Author: Gordon A. Fox
Publisher: OUP Oxford
ISBN: 0191652881
Size: 52.20 MB
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The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the availability of new software, have created a new generation of statistical techniques. These have resulted in major recent developments in both our understanding and practice of ecological statistics. This novel book synthesizes a number of these changes, addressing key approaches and issues that tend to be overlooked in other books such as missing/censored data, correlation structure of data, heterogeneous data, and complex causal relationships. These issues characterize a large proportion of ecological data, but most ecologists' training in traditional statistics simply does not provide them with adequate preparation to handle the associated challenges. Uniquely, Ecological Statistics highlights the underlying links among many statistical approaches that attempt to tackle these issues. In particular, it gives readers an introduction to approaches to inference, likelihoods, generalized linear (mixed) models, spatially or phylogenetically-structured data, and data synthesis, with a strong emphasis on conceptual understanding and subsequent application to data analysis. Written by a team of practicing ecologists, mathematical explanations have been kept to the minimum necessary. This user-friendly textbook will be suitable for graduate students, researchers, and practitioners in the fields of ecology, evolution, environmental studies, and computational biology who are interested in updating their statistical tool kits. A companion web site provides example data sets and commented code in the R language.

Handbook Of Research Methods In Abnormal And Clinical Psychology

Author: Dean McKay
Publisher: SAGE
ISBN: 1412916305
Size: 19.16 MB
Format: PDF, ePub, Mobi
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The Handbook of Research Methods in Abnormal and Clinical Psychology presents a diverse range of areas critical to any researcher or student entering the field. It provides valuable information on the foundations of research methods, including validity in experimental design, ethics, and statistical methods. The contributors discuss design and instrumentation for methods that are particular to abnormal and clinical psychology, including behavioral assessment, psychophysiological assessment and observational methods. They also offer details on new advances in research methodology and analysis, such as meta-analysis, taxometric methods, item response theory, and approaches to determining clinical significance. In addition, this volume covers specialty topics within abnormal and clinical psychology from forensic psychology to behavior genetics to treatment outcome methods.

Key Concepts In Measurement

Author: Brian E. Perron
Publisher: Oxford University Press
ISBN: 0190235977
Size: 51.89 MB
Format: PDF
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Measurement refers generally to the process of assigning a numeric value to, or ordering characteristics or traits of, entities under study. Measurement is necessary for building and testing theory, specifying problems, and defining goals. It is arguably one of the most important and diffcult tasks in social work research. Social work researchers who are not expert in developing, selecting, and using measures will not be able to contribute maximally to the social work knowledge base. Such knowledge and skills related to measurement ultimately determines the extent to which social work research can effectively inform social policy and social work interventions. This book is to serve as a guide for developing, selecting, and using measures in social work research. In particular, this book provides a detailed review of contemporary validity theory; an update on the major issues of reliability; common errors in measurement of latent variables; and suggestions on measurement of social networks and collectives. An important theme of this book is the focus on the creative potential of measurement - that is, helping social work researchers think about the wide variety of ways that social work concepts can be measured. Reflecting on these differences raises questions about underlying assumptions that in turn inspires creative theoretical insights. Rather than seeing measurement as simply a task to be completed in the research process, we will encourage the reader to think creatively about measurement and theory. This book also addresses the interdependency of measurement and theory construction. In other words, this book covers how measurement and theory are connected in two different ways. First, every measure has its own working theory that relates the measure to the concept being measured. Second, theory construction is dependent on measurement. What we learn using a given measure could be different if a concept was measured in a different way.