Автор: Liu, Xing Название: Categorical data analysis and multilevel modeling using r ISBN: 1544324901 ISBN-13(EAN): 9781544324906 Издательство: Sage Publications Рейтинг: Цена: 120390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Categorical Data Analysis and Multilevel Modeling Using Rprovides a practical guide to regression techniques for analyzing binary, ordinal, nominal, and count response variables using the R software. Author Xing Liu offers a unified framework for both single-level and multilevel modeling of categorical and count response variables with both frequentist and Bayesian approaches. Each chapter demonstrates how to conduct the analysis using R, how to interpret the models, and how to present the results for publication. A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.
Автор: Grimm Kevin J., Ram Nilam, Estabrook Ryne Название: Growth Modeling: Structural Equation and Multilevel Modeling Approaches ISBN: 1462526063 ISBN-13(EAN): 9781462526062 Издательство: Taylor&Francis Рейтинг: Цена: 75530.00 T Наличие на складе: Невозможна поставка. Описание: Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model`s results. Pedagogical Features: *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader`s own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book`s examples, along with additional code in SAS/R for linear mixed-effects modeling.
Автор: Ronald H Heck, Scott Thomas, Lynn Tabata Название: Multilevel Modeling of Categorical Outcomes Using IBM SPSS ISBN: 1848729553 ISBN-13(EAN): 9781848729551 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Невозможна поставка. Описание: This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.
Автор: Sonya Bahar Название: The Essential Tension ISBN: 940241052X ISBN-13(EAN): 9789402410525 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Part III addresses experimental studies of cooperation and competition, as well as controversial ideas such as the evolution of evolvability and Stephen Jay Gould`s suggestion that "spandrels" at one level of selection serve as possible sources of variability for the next higher level.
Автор: Silva, Bruno Castanho Название: Multilevel structural equation modeling ISBN: 1544323050 ISBN-13(EAN): 9781544323053 Издательство: Sage Publications Рейтинг: Цена: 39060.00 T Наличие на складе: Поставка под заказ. Описание: Multilevel Structural Equation Modeling by Bruno Castanho Silva, Constantin Manuel Bosancianu, and Levente Littvay 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.
Автор: Heck, Ronald , Thomas, Scott L. Название: An Introduction to Multilevel Modeling Techniques ISBN: 0367182440 ISBN-13(EAN): 9780367182441 Издательство: Taylor&Francis Рейтинг: Цена: 59190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes.
Название: Advanced Structural Equation Modeling ISBN: 1138966045 ISBN-13(EAN): 9781138966048 Издательство: Taylor&Francis Рейтинг: Цена: 50010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: By focusing primarily on the application of structural equation modeling (SEM) techniques in example cases and situations, this book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. The book was written for a broad audience crossing many disciplines, assumes an understanding of graduate level multivariate statistics, including an introduction to SEM.
Название: Small Sample Size Solutions (Open Access) ISBN: 0367222221 ISBN-13(EAN): 9780367222222 Издательство: Taylor&Francis Рейтинг: Цена: 39800.00 T Наличие на складе: Невозможна поставка. Описание: This unique resource provides guidelines and tools for implementing solutions to issues that arise in small sample research. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology, to psychology, marketing, and economics.
Автор: Heck, Ronald , Thomas, Scott L. Название: An Introduction to Multilevel Modeling Techniques ISBN: 0367182424 ISBN-13(EAN): 9780367182427 Издательство: Taylor&Francis Рейтинг: Цена: 178640.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes.
Автор: Jeffrey R. Harring, Laura M. Stapleton, S. Natasha Beretvas Название: Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications ISBN: 1681233282 ISBN-13(EAN): 9781681233284 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 94250.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Examines the latest methodological innovations, refinements and state-of-the-art developments and perspectives in the analysis of multilevel data, including current best practices of standard techniques. This volume will be particularly useful to researchers in educational policy, educational psychology including school psychology and special education, and clinical psychology.
Автор: Smith Robert B. Название: Multilevel Modeling of Social Problems: A Causal Perspective ISBN: 9048198542 ISBN-13(EAN): 9789048198542 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Uniquely focusing on intersections of social problems, multilevel statistical modeling, and causality; These models are also referred to as hierarchical linear models (HLMs) or mixed models.
Автор: Robert B. Smith Название: Multilevel Modeling of Social Problems ISBN: 9401784310 ISBN-13(EAN): 9789401784313 Издательство: Springer Рейтинг: Цена: 222670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Uniquely focusing on intersections of social problems, multilevel statistical modeling, and causality; These models are also referred to as hierarchical linear models (HLMs) or mixed models.
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