Multilevel Modeling Methods With Introductory And Advanced Applications
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Multilevel Modeling Methods With Introductory And Advanced Applications
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Author : Ann A. O'Connell
language : en
Publisher: IAP
Release Date : 2022-03-01
Multilevel Modeling Methods With Introductory And Advanced Applications written by Ann A. O'Connell and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Education categories.
Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation. In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs. Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.
An Introduction To Multilevel Modeling Techniques
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Author : Ronald H. Heck
language : en
Publisher: Psychology Press
Release Date : 1999-11-01
An Introduction To Multilevel Modeling Techniques written by Ronald H. Heck and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-11-01 with Computers categories.
This book provides a broad overview of basic multilevel modeling issues and illustrates techniques building analyses around several organizational data sets. Although the focus is primarily on educational and organizational settings, the examples will help the reader discover other applications for these techniques. Two basic classes of multilevel models are developed: multilevel regression models and multilevel models for covariance structures--are used to develop the rationale behind these models and provide an introduction to the design and analysis of research studies using two multilevel analytic techniques--hierarchical linear modeling and structural equation modeling.
Multilevel Analysis
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Author : Joop J. Hox
language : en
Publisher: Routledge
Release Date : 2010-09-13
Multilevel Analysis written by Joop J. Hox and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-13 with Psychology categories.
This practical introduction helps readers apply multilevel techniques to their research. Noted as an accessible introduction, the book also includes advanced extensions, making it useful as both an introduction and as a reference to students, researchers, and methodologists. Basic models and examples are discussed in non-technical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines. For example, readers will find data sets on stress in hospitals, GPA scores, survey responses, street safety, epilepsy, divorce, and sociometric scores, to name a few. The data sets are available on the website in SPSS, HLM, MLwiN, LISREL and/or Mplus files. Readers are introduced to both the multilevel regression model and multilevel structural models. Highlights of the second edition include: Two new chapters—one on multilevel models for ordinal and count data (Ch. 7) and another on multilevel survival analysis (Ch. 8). Thoroughly updated chapters on multilevel structural equation modeling that reflect the enormous technical progress of the last few years. The addition of some simpler examples to help the novice, whilst the more complex examples that combine more than one problem have been retained. A new section on multivariate meta-analysis (Ch. 11). Expanded discussions of covariance structures across time and analyzing longitudinal data where no trend is expected. Expanded chapter on the logistic model for dichotomous data and proportions with new estimation methods. An updated website at http://www.joophox.net/ with data sets for all the text examples and up-to-date screen shots and PowerPoint slides for instructors. Ideal for introductory courses on multilevel modeling and/or ones that introduce this topic in some detail taught in a variety of disciplines including: psychology, education, sociology, the health sciences, and business. The advanced extensions also make this a favorite resource for researchers and methodologists in these disciplines. A basic understanding of ANOVA and multiple regression is assumed. The section on multilevel structural equation models assumes a basic understanding of SEM.
Multilevel Analysis
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Author : Tom A. B. Snijders
language : en
Publisher: SAGE
Release Date : 1999
Multilevel Analysis written by Tom A. B. Snijders and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Mathematics categories.
Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.
Structural Equation Modeling
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Author : Gregory R. Hancock
language : en
Publisher: IAP
Release Date : 2013-03-01
Structural Equation Modeling written by Gregory R. Hancock and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-01 with Education categories.
Sponsored by the American Educational Research Association's Special Interest Group for Educational Statisticians This volume is the second edition of Hancock and Mueller’s highly-successful 2006 volume, with all of the original chapters updated as well as four new chapters. The second edition, like the first, is intended to serve as a didactically-oriented resource for graduate students and research professionals, covering a broad range of advanced topics often not discussed in introductory courses on structural equation modeling (SEM). Such topics are important in furthering the understanding of foundations and assumptions underlying SEM as well as in exploring SEM, as a potential tool to address new types of research questions that might not have arisen during a first course. Chapters focus on the clear explanation and application of topics, rather than on analytical derivations, and contain materials from popular SEM software.
Introducing Multilevel Modeling
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Author : Ita G G Kreft
language : en
Publisher: SAGE
Release Date : 1998-04-07
Introducing Multilevel Modeling written by Ita G G Kreft and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04-07 with Social Science categories.
This is the first accessible and practical guide to using multilevel models in social research. Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models. While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling. The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key features include the use of worked examples using real data sets, analyzed using the leading computer package for multilevel modeling - "MLn." Discussion site at: http: \www.stat.ucla.eduphplibw-agoraw-agora.phtml?bn=Sagebook Data files mentioned in the book are available from: http: \www.stat.ucla.edu deleeuwsagebook
Multilevel Modeling Using R
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Author : W. Holmes Finch
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2019
Multilevel Modeling Using R written by W. Holmes Finch and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Multivariate analysis categories.
This book focuses on presenting the theory and practice of major multilevel modelling techniques in a variety of contexts, using R as the software tool, and demonstrating the various functions available for these analyses in R.
Multilevel Modeling In Plain Language
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Author : Karen Robson
language : en
Publisher: SAGE
Release Date : 2015-11-02
Multilevel Modeling In Plain Language written by Karen Robson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-02 with Social Science categories.
Have you been told you need to do multilevel modeling, but you can′t get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense? Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated. This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.
Hierarchical Linear Modeling
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Author : G. David Garson
language : en
Publisher: SAGE
Release Date : 2013
Hierarchical Linear Modeling written by G. David Garson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Mathematics categories.
This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.
Multilevel Modeling
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Author : Douglas A. Luke
language : en
Publisher: SAGE
Release Date : 2004-07-08
Multilevel Modeling written by Douglas A. Luke and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-07-08 with Mathematics categories.
Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.