Multilevel modeling methods with introductory and advanced applications / Ann A. O'Connell, D. Betsy McCoach, Bethany A. Bell.

Format Electronic
PublicationCharlotte, NC : IAP/Information Age Publishing, Incorporated, 2022.
Description1 online resource.
Supplemental ContentEBSCOhost
Subjects

Other author/creatorO'Connell, Ann A., editor. https://id.oclc.org/worldcat/entity/E39PCjyWMTcCjfM4xBPPDhCh9C
Other author/creatorMcCoach, D. Betsy, editor. https://id.oclc.org/worldcat/entity/E39PCjyBcTGQPTfHQgVMP9cRXd
Other author/creatorBell, Bethany A., editor.
Other author/creatorProQuest (Firm) https://id.oclc.org/worldcat/entity/E39QQPVp7VPY8D8TQ8yxKjyRCF
SeriesQuantitative Methods in Education and the Behavioral Sciences
Quantitative methods in education and the behavioral sciences. ^A1489779
Contents Introduction to multilevel modeling methods: pedagogy and context / Ann. A O'Connell, D. Betsy McCoach, and Bethany A. Bell -- Section1. Organizational Data -- Introduction to multilevel models for organizational data / Bethany A. Bell and Jason A. Schoeneberger -- Evaluation of model fit and adequacy / D. Betsy McCoach, Sarah D. Newton, Anthony J. Gambino -- Causal inference in multilevel settings / Chris Rhoads and Eva Yujia Li -- Statistical power for linear multilevel models / Jessaca Spybrook, Benjamin M. Kelcey, and Nianbo Dong -- Cross-classified random-effects models / Audrey J. Leroux and S. Natasha Beretvas -- Multilevel logistic and ordinal models / Ann A. O'Connell, Meng-Ting Lo, Jessica Goldstein, H. Jane Rogers, and C.-Y. Joanne Peng -- Single and multilevel models for counts / Ann A. O'Connell, Nivedita Bhaktha, and Jing Zhang -- Section 2. Longitudinal Data -- Individual growth curve models for longitudinal data / D. Betsy McCoach, Bethany A. Bell, and Aarti P. Bellara -- Modeling nonlinear longitudinal change with mixed effects models / Jeffrey R. Harring and Shelley A. Blozis -- Within-subject residual variance-covariance structures in longitudinal data analysis / Minjung Kim, Hsien-Yuan Hsu, and Oi-man Kwok -- Modeling variation in intensive longitudinal data / Donald Hedeker and Robin J. Mermelstein -- Section 3. Design and Special Issues -- Using large-scale complex sample datasets in multilevel modeling / Laura M. Stapleton and Scott L. Thomas -- Common measurement issues in a multilevel framework / Brian F. French, W. Holmes Finch, and Thao Vo -- Missing data handling for multilevel data / Craig K. Enders and Timothy Hayes -- Multilevel mediation analysis / Nicholas J. Rockwood and Andrew F. Hayes -- Reporting results of multilevel designs / John M. Ferron, Yan Wang, Zhiyao Yi, Yue Yin, Eunsook Kim, and Robert F. Dedrick.
Abstract 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 inclusionof 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 methodologicalal and applied readings.-- Provided by publisher.
Bibliography noteIncludes bibliographical references.
Source of descriptionDescription based on online resource; title from digital title page (viewed on July 14, 2022).
Issued in other formPrint version: O'Connell, Ann A. Multilevel Modeling Methods with Introductory and Advanced Applications Charlotte, NC : Information Age Publishing, Incorporated,c2022 9781648028717
LCCN 2022004080
ISBN9781648028731 electronic book
ISBN164802873X electronic book
ISBNpaperback
ISBNpaperback
ISBNhardcover
ISBNhardcover

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