The handbook of multilevel theory, measurement, and analysis.

This handbook provides guidance to organizational and social science scholars interested in pursuing multilevel research. Organizational relationships are complex. Employees do their work as individuals, but also as members of larger teams. They exist within various social networks, both within and spanning organizations. Multilevel theory is at the core of the organizational sciences, and unpacking multilevel relationships is fundamental to the challenges faced within these disciplines. Yet, guidance about how to pursue multilevel research has often been siloed within subdomains. In this book, prominent experts on multilevel research guide scholars in the social and behavioral sciences who wish to consider the implications that multilevel research may have for their work. Although the majority of contributors to this handbook have backgrounds in the organizational sciences, the chapters are accessible to researchers from a wide array disciplines including, but not limited to, communication, education, sociology, psychology, and management. Organizational relationships are complex. Employees do their work as individuals, but also as members of larger teams. They exist within various social networks, both within and spanning organizations. Multilevel theory is at the core of the organizational sciences, and unpacking multilevel relationships is fundamental to the challenges faced within these disciplines. Yet, guidance about how to pursue multilevel research has often been siloed within subdomains. In this book, Stephen E. Humphrey and James M. LeBreton bring together experts on multilevel research who guide scholars in the social and behavioral sciences who wish to consider the implications that multilevel research may have for their work. Although the majority of contributors to this handbook have backgrounds in the organizational sciences, the chapters are accessible to researchers from a variety of disciplines including communication, education, sociology, psychology, and management. This book contains the following chapters: (1) On Finding Your Level (Stanley M. Gully and Jean M. Phillips); (2) Contextualizing Context in Organizational Research (Cheri Ostroff); (3) Ask Not What the Study of Context Can Do for You: Ask What You Can Do for the Study of Context (Rustin D. Meyer, Katie England, Elnora D. Kelly, Andrew Helbling, MinShuou Li, and Donna Outten); (4) The Only Constant Is Change: Expanding Theory by Incorporating Dynamic Properties Into One's Models (Matthew A. Cronin and Jeffrey B. Vancouver); (5) The Means Are the End: Complexity Science in Organizational Research (Juliet R. Aiken, Paul J. Hanges, and Tiancheng Chen); (6) The Missing Levels of Microfoundations: A Call for Bottom-Up Theory and Methods (Robert E. Ployhart and Jonathan L. Hendricks); (7) Multilevel Emergence in Work Collectives (John E. Mathieu and Margaret M. Luciano); (8) Multilevel Thoughts on Social Networks (Daniel J. Brass and Stephen P. Borgatti); (9) Conceptual Foundations of Multilevel Social Networks (Srikanth Paruchuri, Martin C. Goossen, and Corey Phelps); (10) Introduction to Data Collection in Multilevel Research (Le Zhou, Yifan Song, Valeria Alterman, Yihao Liu, and Mo Wang); (11) Construct Validation in Multilevel Studies (Andrew T. Jebb, Louis Tay, Vincent Ng, and Sang Woo); (12) Multilevel Measurement: Agreement, Reliability, and Nonindependence (Dina V. Krasikova and James M. LeBreton); (13) Looking Within: An Examination, Combination, and Extension of Within-Person Methods Across Multiple Levels of Analysis (Daniel J. Beal and Allison S. Gabriel); (14) Power Analysis for Multilevel Research (Charles A. Scherbaum and Erik Pesner); (15) Explained Variance Measures for Multilevel Models (David M. LaHuis, Caitlin E. Blackmore, and Kinsey B. Bryant-Lees); (16) Missing Data in Multilevel Research (Simon Grund, Oliver Lüdtke, and Alexander Robitzsch); (17) A Primer on Multilevel (Random Coefficient) Regression Modeling (Levi K. Shiverdecker and James M. LeBreton); (18) Dyadic Data Analysis (Andrew P. Knight and Stephen E. Humphrey); (19) A Primer on Multilevel Structural Modeling: User-Friendly Guidelines (Robert J. Vandenberg and Hettie A. Richardson); (20) Moderated Mediation in Multilevel Structural Equation Models: Decomposing Effects of Race on Math Achievement Within Versus Between High Schools in the United States (Michael J. Zyphur, Zhen Zhang, Kristopher J. Preacher, and Laura J. Bird); (21) Anything but Normal: The Challenges, Solutions, and Practical Considerations of Analyzing Nonnormal Multilevel Data (Miles A. Zachary, Curt B. Moore, and Gary A. Ballinger); (22) A Temporal Perspective on Emergence: Using Three-Level Mixed-Effects Models to Track Consensus Emergence in Groups (Jonas W. B. Lang and Paul D. Bliese); (23) Social Network Effects: Computational Modeling of Network Contagion and Climate Emergence (Daniel A. Newman and Wei Wang); (24) Cross-Level Models (Francis J. Yammarino and Janaki Gooty); and (25) Panel Interview: Reflections on Multilevel Theory, Measurement, and Analysis (Michael E. Hoffman, David Chan, Gilad Chen, Fred Dansereau, Denise Rousseau, and Benjamin Schneider) Multilevel theory -- On finding your level / Stanley M. Gully and Jean M. Phillips -- Contextualizing context in organizational research / Cheri Ostroff -- Ask not what the study of context can do for you : ask what you can do for the study of context / Rustin D. Meyer, Katie England, Elnora D. Kelly, Andrew Helbling, MinShuou Li, and Donna Outten -- The only constant is change : expanding theory by incorporating dynamic properties into one's models / Matthew A. Cronin and Jeffrey B. Vancouver -- The means are the end : complexity science in organizational research / Juliet R. Aiken, Paul J. Hanges, and Tiancheng Chen -- The missing levels of microfoundations: a call for bottom-up theory and methods / Robert E. Ployhart and Jonathan Hendricks -- Multilevel emergence in work collectives / John E. Mathieu and Margaret M. Luciano -- Multilevel thoughts on social networks / Daniel J. Brass and Stephen P. Borgatti -- Conceptual foundations of multilevel social networks / Srikanth Paruchuri, Martin C. Goossen, and Corey Phelps -- Multilevel measurement and design -- Introduction to data collection in multilevel research / Le Zhou, Yifan Song, Valeria Alterman, Yihao Liu, and Mo Wang -- Construct validation in multilevel studies / Andrew T. Jebb, Louis Tay, Vincent Ng, and Sang Eun Woo -- Multilevel measurement : agreement, reliability, and nonindependence / Dina V. Krasikova and James M. LeBreton -- Looking within : an examination, combination, and extension of within-person methods across multiple levels of analysis / Daniel J. Beal and Allison S. Gabriel -- Power analysis for multilevel research / Charles A. Scherbaum and Erik Pesner -- Explained variance measures for multilevel models / David M. LaHuis, Caitlin E. Blackmore, and Kinsey B. Bryant-Lees -- Missing data in multilevel research / Simon Grund, Oliver Lüdtke, and Alexander Robitzsch -- Multilevel analysis -- A primer on multilevel (random coefficient) regression modeling / Levi Shiverdecker and James M. LeBreton -- Dyadic data analysis / Andrew P. Knight and Stephen A. Humphrey -- A primer on multilevel structural equation modeling : user-friendly guidelines / Robert J. Vandenberg and Hettie A. Richardson -- Moderated mediation in multilevel sem: decomposing effects of race on math achievement within versus between high schools in the united states / Michael J. Zyphur, Zhen Zhang, Kristopher J. Preacher, and Laura J. Bird -- Anything but normal : the challenges, solutions, and practical considerations of analyzing nonnormal multilevel data / Miles A. Zachary, Curt B. Moore, and Gary A. Ballinger -- A temporal perspective on emergence : using 3-level mixed effects models to track consensus emergence in groups / Jonas W.B. Lang and Paul D. Bliese -- Social network effects: computational modeling of network contagion and climate emergence -- Daniel A. Newman and Wei Wang -- Reflections on multilevel research -- Cross-level models / Francis J. Yammarino and Janaki Gooty -- Panel interview : reflections on multilevel theory, measurement, and analysis / Michael E. Hoffman, David Chan, Gilad Chen, Fred Dansereau, Denise Rousseau, and Benjamin Schneider The Handbook of Multilevel Theory, Measurement, and Analysis Contents 5 Contributors 7 Introduction 13 On Finding Your Level 19 Contextualizing Context In Organizational Research 47 Ask Not What The Study Of Context Can Do For You: Ask What You Can Do For The Study Of Context 74 The Only Constant Is Change: Expanding Theory By Incorporating Dynamic Properties Into One’s Models 96 The Means Are The End: Complexity Science In Organizational Research 122 The Missing Levels Of Microfoundations: A Call For Bottom-up Theory And Methods 148 Multilevel Emergence In Work Collectives 170 Multilevel Thoughts On Social Networks 194 Conceptual Foundations Of Multilevel Social Networks 208 Introduction To Data Collection In Multilevel Research 229 Construct Validation In Multilevel Studies 257 Multilevel Measurement: Agreement, Reliability, And Nonindependence 283 Looking Within: An Examination, Combination, And Extension Of Within-person Methods Across Multiple Levels Of Analysis 309 Power Analysis For Multilevel Research 332 Explained Variance Measures For Multilevel Models 356 Missing Data In Multilevel Research 368 A Primer On Multilevel (random Coefficient) Regression Modeling 390 Dyadic Data Analysis 424 A Primer On Multilevel Structural Modeling: User-friendly Guidelines 449 Moderated Mediation In Multilevel Structural Equation Models Decomposing Effects Of Race On Math Achievement Within Versus Betwe 473 Anything But Normal: The Challenges, Solutions, And Practical Considerations Of Analyzing Nonnormal Multilevel Data 495 A Temporal Perspective On Emergence: Using Three-level Mixed-effects Models To Track Consensus Emergence In Groups 518 Social Network Effects: Computational Modeling Of Network Contagion And Climate Emergence 540 Cross-level Models 560 Panel Interview: Reflections On Multilevel Theory, Measurement, And Analysis 583 Index 605 About The Editors 633 The Handbook of Multilevel Theory,Measurement,and Analysis "The purpose of this handbook is to provide guidance for scholars working in the social and behavioral sciences who wish to consider the implications that multilevel research (i.e., theory, measurement, and analysis) may have for their research programs. The chapters in the book are accessible to researchers from a wide array of research disciplines including (but not limited to) communication, education, sociology, psychology (clinical, developmental, industrial, social), management (strategy, human resources, organizational behavior), and nursing. The book is organized into four parts comprising twenty five chapters. Part I focuses on providing guidance on how to improve theory by integrating a multilevel perspective. Part II transition from focusing largely on issues related to multilevel theory, to a discussion of issues related to multilevel measurement and research design. It is important for those readers who have specified their theory and are now ready to set about collecting data to test it. Part III deals with questions of analysis on multilevel regression analyses, dyadic data analysis, moderated mediation, and network analysis. Part IV consists of two concluding chapters which provide perspective on the development of multilevel research. The first concluding chapter begins by providing a historical perspective on cross-level models, examining the similarities and differences in how the concept of "cross-level models" has been applied by various groups of researchers. It then transitions to the presentation of an integrative cross-level model, discussing its applicability to theory building and testing within the organizational sciences."--Preface. (PsycINFO Database Record (c) 2018 APA, all rights reserved) This inclusive, thorough, and practical handbook brings together prominent experts who describe how to conduct multilevel research. Chapters show readers how to begin thinking as multilevel scholars through discussions of context, dynamics, and complexity, and guide readers through the nuances of research design and analysis. Although most contributors have backgrounds in the organizational sciences, chapters are accessible to graduate students and researchers from a wide array of research disciplines, such as communication, education, sociology, psychology, and management.
  Provides guidance to organisational and social science scholars interested in pursuing multilevel research. Multilevel theory is at the core of the organizational sciences, and unpacking multilevel relationships is fundamental to the challenges faced within these disciplines. This handbook shows scholars how to conduct multilevel research. Chapters discuss the importance of context, dynamics, and complexity, and guide readers through the nuances of research design and analysis.