The Handbook of Multilevel Theory, Measurement, and Analysis

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Sonst. Personen	Humphrey, Stephen E. (Hrsg.); LeBreton, James M. (Hrsg.)
Titel	The Handbook of Multilevel Theory, Measurement, and Analysis
Quelle	(2019), (637 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
ISBN	978-1-4338-3001-3
Schlagwörter	Leitfaden; Hierarchical Linear Modeling; Theories; Institutional Research; Social Networks; Data Collection; Construct Validity; Measurement; Statistical Analysis; Data Analysis; Structural Equation Models; Research Design; High Schools; Mathematics Achievement; Race + Suchen Sie Ihr Suchwort? Theory; Theorie; Institutionelle Forschung; Social network; Soziales Netzwerk; Data capture; Datensammlung; Messverfahren; Statistische Analyse; Auswertung; Forschungsdesign; High school; Oberschule; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Rasse; Abstammung
Abstract	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). (ERIC).
Anmerkungen	APA Books. Available from: American Psychological Association. 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5500; e-mail: books@apa.org; Web site: http://www.apa.org/pubs/books/index.aspx
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01