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.
 

Stephen E. Humphrey, PhD, is a professor of management and the Smeal College Executive Programs Fellow in the Smeal College of Business at Pennsylvania State University. His research focuses on social relations at work, with a primary focus on teamwork, the drivers of team success, and the development of relationships within teams. Much of his work unpacks the microdynamics of teams, approaching research questions using a multilevel, multiperiod, multitheoretical lens. Dr. Humphrey’s research has been published in various management and psychology outlets, including Academy of Management Journal, Journal of Applied Psychology, Journal of Personality, Personnel Psychology, and Organizational Behavior and Human Decision Processes. He also has authored numerous book chapters. Finally, Dr. Humphrey previously served as the associate editor at Organizational Psychology Review and currently serves on the editorial boards of Academy of Management Journal and Journal of Applied Psychology.

James M. LeBreton, PhD, is a professor of psychology at Pennsylvania State University. His research focuses on the theory and measurement of implicit motives (e.g., motive to aggress, motive to achieve) and understanding how implicit motives are related to a range of work-related behaviors (e.g., counterproductive work behavior, leadership, team performance). Dr. LeBreton’s methodological work focuses on topics such as assessing interrater agreement and reliability, analyzing longitudinal and multilevel data, and assessing the relative importance of predictors in regression models. In addition to authoring a book on implicit personality and several book chapters, Dr. LeBreton has published articles in outlets such as Current Directions in Psychological Science, Journal of Applied Psychology, Journal of Management, Personnel Psychology, Perspectives on Psychological Science, Psychological Methods, and Psychological Science. In 2009, he was awarded the Early Career Award from the Academy of Management’s Research Methods Division and the Center for the Advancement of Research Methods and Analysis. In 2013, he was elected Fellow of the American Psychological Association and the Society for Industrial and Organizational Psychology. Dr. LeBreton has served on the Executive Committee for the Research Methods Division of the Academy of Management and the Scientific Affairs Committee for the Society for Industrial and Organizational Psychology. He currently serves on the editorial boards of Human Performance, Journal of Applied Psychology, and Journal of Management. From 2014 to 2017, Dr. LeBreton served as the editor-in-chief for Organizational Research Methods. In addition, he is a regular instructor and presenter for the Consortium for the Advancement of Research Methods and Analysis.

Introduction
Part I: Multilevel Theory
Chapter 1: On Finding Your Level
Stanley M. Gully and Jean M. Phillips
Chapter 2: Contextualizing Context in Organizational Research
Cheri Ostroff
Chapter 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
Chapter 4: The Only Constant Is Change: Expanding Theory by Incorporating Dynamic Properties Into One’s Models
Matthew A. Cronin and Jeffrey B. Vancouver
Chapter 5: The Means Are the End: Complexity Science in Organizational Research
Juliet R. Aiken, Paul J. Hanges, and Tiancheng Chen
Chapter 6: The Missing Levels of Microfoundations: A Call for Bottom-Up Theory and Methods
Robert E. Ployhart and Jonathan Hendricks
Chapter 7: Multilevel Emergence in Work Collectives
John E. Mathieu and Margaret M. Luciano
Chapter 8: Multilevel Thoughts on Social Networks
Daniel J. Brass and Stephen P. Borgatti
Chapter 9: Conceptual Foundations of Multilevel Social Networks
Srikanth Paruchuri, Martin C. Goossen, and Corey Phelps
Part II: Multilevel Measurement and Design
Chapter 10: Introduction to Data Collection in Multilevel Research
Le Zhou, Yifan Song, Valeria Alterman, Yihao Liu, and Mo Wang
Chapter 11: Construct Validation in Multilevel Studies
Andrew T. Jebb, Louis Tay, Vincent Ng, and Sang Woo
Chapter 12: Multilevel Measurement: Agreement, Reliability, and Nonindependence
Dina V. Krasikova and James M. LeBreton
Chapter 13: Looking Within: An Examination, Combination, and Extension of Within-Person Methods Across Multiple Levels of Analysis
Daniel J. Beal and Allison S. Gabriel
Chapter 14: Power Analysis for Multilevel Research
Charles A. Scherbaum and Erik Pesner
Chapter 15: Explained Variance Measures for Multilevel Models
David M. LaHuis, Caitlin E. Blackmore, and Kinsey B. Bryant-Lees
Chapter 16: Missing Data in Multilevel Research
Simon Grund, Oliver Lüdtke, and Alexander Robitzsch
Part III: Multilevel Analysis
Chapter 17: A Primer on Multilevel (Random Coefficient) Regression Modeling
Levi K. Shiverdecker and James M. LeBreton
Chapter 18: Dyadic Data Analysis
Andrew P. Knight and Stephen E. Humphrey
Chapter 19: A Primer on Multilevel Structural Modeling: User-Friendly Guidelines
Robert J. Vandenberg and Hettie A. Richardson
Chapter 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
Chapter 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
Chapter 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
Chapter 23: Social Network Effects: Computational Modeling of Network Contagion and Climate Emergence
Daniel A. Newman and Wei Wang
Part IV. Reflections on Multilevel Research
Chapter 24: Cross-Level Models
Francis J. Yammarino and Janaki Gooty
Chapter 25: Panel Interview: Reflections on Multilevel Theory, Measurement, and Analysis
Michael E. Hoffman, David Chan, Gilad Chen, Fred Dansereau, Denise Rousseau, and Benjamin Schneider
Index
About the Editors