Multilevel Analysis for Applied Research

It's Just Regression!

Author: Robert Bickel

Publisher: Guilford Press

ISBN: 1609181069

Category: Psychology

Page: 355

View: 1280

This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical techniques they already know, Robert Bickel emphasizes the parallels with more familiar regression models, shows how to do multilevel modeling using SPSS, and demonstrates how to interpret the results. He discusses the strengths and limitations of multilevel analysis and explains specific circumstances in which it offers (or does not offer) methodological advantages over more traditional techniques. Over 300 dataset examples from research on educational achievement, income attainment, voting behavior, and other timely issues are presented in numbered procedural steps.

Advances in Mixed Methods Research

Theories and Applications

Author: Manfred Max Bergman

Publisher: SAGE

ISBN: 0857024310

Category: Social Science

Page: 200

View: 7009

Advances in Mixed Methods Research provides an essential introduction to the fast-growing field of mixed methods research. Bergman's book examines the current state of mixed-methods research, exploring exciting new ways of conceptualizing and conducting empirical research in the social and health sciences. Contributions from the world's leading experts in qualitative, quantitative, and mixed methods approaches are brought together, clearing the way for a more constructive approach to social research. These contributions cover the main practical and methodological issues and include a number of different visions of what mixed methods research is. The discussion also covers the use of mixed methods in a diverse range of fields, including sociology, education, politics, psychology, computational science and methodology. This book represents an important contribution to the ongoing debate surrounding the use of mixed methods in the social sciences and health research, and presents a convincing argument that the conventional, paradigmatic view of qualitative and quantitative research is outdated and in need of replacement. It will be essential reading for anyone actively engaged in qualitative, quantitative and mixed methods research and for students of social research methods. Manfred Max Bergman is Chair of Methodology and Political Sociology at the University of Basel.

Multilevel Analysis

Techniques and Applications, Third Edition

Author: Joop J. Hox,Mirjam Moerbeek,Rens van de Schoot

Publisher: Routledge

ISBN: 1317308670

Category: Psychology

Page: 348

View: 9362

Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical 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 including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.

Multilevel Modeling

Author: Douglas A. Luke

Publisher: SAGE

ISBN: 9780761928799

Category: Mathematics

Page: 79

View: 2396

A practical introduction to multi-level modelling, this book offers an introduction to HLM & illustrations of how to use this technique to build models for hierarchical & longitudinal data.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Author: Andrew Gelman,Jennifer Hill

Publisher: Cambridge University Press

ISBN: 9780521686891

Category: Mathematics

Page: 625

View: 9275

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Hierarchical Linear Models

Applications and Data Analysis Methods

Author: Stephen W. Raudenbush,Anthony S. Bryk

Publisher: SAGE

ISBN: 9780761919049

Category: Mathematics

Page: 485

View: 1097

Popular in its first edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been updated to include: an intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication; a new section on multivariate growth models; a discussion of research synthesis or meta-analysis applications; aata analytic advice on centering of level-1 predictors, and new material on plausible value intervals and robust standard estimators.

Applied Missing Data Analysis

Author: Craig K. Enders

Publisher: Guilford Press

ISBN: 1606236407

Category: Psychology

Page: 377

View: 4241

Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website ( includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists.

Data Analysis with Mplus

Author: Christian Geiser

Publisher: Guilford Press

ISBN: 1462507824

Category: Psychology

Page: 305

View: 1399

A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to specify different types of models in Mplus syntax and address typical caveats--for example, assessing measurement invariance in longitudinal SEMs. Coverage includes path and factor analytic models as well as mediational, longitudinal, multilevel, and latent class models. Specific programming tips and solution strategies are presented in boxes in each chapter. The companion website ( features data sets, annotated syntax files, and output for all of the examples. Of special utility to instructors and students, many of the examples can be run with the free demo version of Mplus.

Multilevel Analysis

An Introduction to Basic and Advanced Multilevel Modeling

Author: Tom A B Snijders,Roel J Bosker

Publisher: SAGE

ISBN: 144625433X

Category: Reference

Page: 368

View: 3341

The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.

The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2

Statistical Analysis

Author: Todd D. Little

Publisher: Oxford University Press

ISBN: 0199934894

Category: Medical

Page: 736

View: 8597

The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.

Interaction Effects in Multiple Regression

Author: James Jaccard,Robert Turrisi

Publisher: SAGE Publications

ISBN: 1544332572

Category: Social Science

Page: 104

View: 2781

Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new addition will expand the coverage on the analysis of three way interactions in multiple regression analysis. Learn more about "The Little Green Book" - QASS Series! Click Here

Multilevel Modeling in Plain Language

Author: Karen Robson,David Pevalin

Publisher: SAGE

ISBN: 1473934311

Category: Social Science

Page: 160

View: 7568

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.

Multilevel Modeling Using R

Author: W. Holmes Finch,Jocelyn E. Bolin,Ken Kelley

Publisher: CRC Press

ISBN: 1466515864

Category: Mathematics

Page: 230

View: 6119

A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment. After reviewing standard linear models, the authors present the basics of multilevel models and explain how to fit these models using R. They then show how to employ multilevel modeling with longitudinal data and demonstrate the valuable graphical options in R. The book also describes models for categorical dependent variables in both single level and multilevel data. The book concludes with Bayesian fitting of multilevel models. For those new to R, the appendix provides an introduction to this system that covers basic R knowledge necessary to run the models in the book. Through the R code and detailed explanations provided, this book gives you the tools to launch your own investigations in multilevel modeling and gain insight into your research.

Handbook of Advanced Multilevel Analysis

Author: Joop Hox,J. Kyle Roberts

Publisher: Psychology Press

ISBN: 113695127X

Category: Education

Page: 408

View: 9588

This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.

Dyadic Data Analysis

Author: David A. Kenny,Deborah A. Kashy,William L. Cook

Publisher: Guilford Press

ISBN: 1572309865

Category: Social Science

Page: 458

View: 1773

The first book on the subject, this unique resource is comprehensive and authoritative. The authors' approach has wide applications for analyzing data related to couples, siblings, friends, coworkers, parent-child, doctor-patient pairs, and more. They compare and contrast different quantitative methods and evaluate their suitability for diverse situations.

Doing Statistical Mediation and Moderation

Author: Paul E. Jose

Publisher: Guilford Press

ISBN: 1462508219

Category: Psychology

Page: 336

View: 1800

"Written in a friendly, conversational style, this book offers a hands-on approach to statistical mediation and moderation for both beginning researchers and those familiar with modeling. Starting with a gentle review of regression-based analysis, Paul Jose covers basic mediation and moderation techniques before moving on to advanced topics in multilevel modeling, structural equation modeling, and hybrid combinations, such as moderated mediation. User-friendly features include numerous graphs and carefully worked-through examples; "Helpful Suggestions" about procedures and pitfalls; "Knowledge Boxes" delving into special topics, such as dummy coding; and end-of-chapter exercises and problems (with answers). The companion website provides downloadable sample data sets that are used in the book to demonstrate particular analytic strategies, and explains how researchers and students can execute analyses using Jose's online programs, MedGraph and ModGraph. Appendices present SPSS, AMOS, and Mplus syntax for conducting the key types of analyses"--

Multilevel Network Analysis for the Social Sciences

Theory, Methods and Applications

Author: Emmanuel Lazega,Tom A.B. Snijders

Publisher: Springer

ISBN: 3319245201

Category: Social Science

Page: 375

View: 4305

This volume provides new insights into the functioning of organizational, managerial and market societies. Multilevel analysis and social network analysis are described and the authors show how they can be combined in developing the theory, methods and empirical applications of the social sciences. This book maps out the development of multilevel reasoning and shows how it can explain behavior, through two different ways of contextualizing it. First, by identifying levels of influence on behavior and different aggregations of actors and behavior, and complex interactions between context and behavior. Second, by identifying different levels as truly different systems of agency: such levels of agency can be examined separately and jointly since the link between them is affiliation of members of one level to collective actors at the superior level. It is by combining these approaches that this work offers new insights. New case studies and datasets that explore new avenues of theorizing and new applications of methodology are presented. This book will be useful as a reference work for all social scientists, economists and historians who use network analyses and multilevel statistical analyses. Philosophers interested in the philosophy of science or epistemology will also find this book valuable. ​

Theory Construction and Model-building Skills

A Practical Guide for Social Scientists

Author: James Jaccard,Jacob Jacoby

Publisher: Guilford Press

ISBN: 1606233408

Category: Psychology

Page: 391

View: 1873

Meeting a crucial need for graduate students and newly minted researchers, this innovative text provides hands-on tools for generating ideas and translating them into formal theories. It is illustrated with numerous practical examples drawn from multiple social science disciplines and research settings. The authors offer clear guidance for defining constructs, thinking through relationships and processes that link constructs, and deriving new theoretical models (or building on existing ones) based on those relationships. Step by step, they show readers how to use causal analysis, mathematical modeling, simulations, and grounded and emergent approaches to theory construction. A chapter on writing about theories contains invaluable advice on crafting effective papers and grant applications. Useful pedagogical features in every chapter include: Application exercises and concept exercises Lists of key terms and engaging topical boxes Annotated suggestions for further reading. This book is intended for graduate students in a range of disciplines, including psychology, education, sociology, health, and management, as well as social scientists pursing research careers in academic or other settings. It can serve as a primary text in graduate-level courses in theory construction or as a supplemental text in courses on research methodology, theories of a particular discipline, grant writing, or the dissertation.

Quantile Regression

Author: Lingxin Hao,Daniel Q. Naiman

Publisher: SAGE Publications

ISBN: 1483316904

Category: Social Science

Page: 136

View: 4408

Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines. Key Features: Establishes a natural link between quantile regression and inequality studies in the social sciences Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples Includes computational codes using statistical software popular among social scientists Oriented to empirical research