Multilevel modeling methods with introductory and advanced applications /:
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 o...
Gespeichert in:
| Körperschaft: | |
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| Weitere Verfasser: | , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Charlotte, NC :
IAP/Information Age Publishing, Incorporated,
2022.
|
| Schriftenreihe: | Quantitative methods in education and the behavioral sciences.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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 forinstructors, who must continually search for class examples and homeworkproblems. In addition, each chapter provides recommendations for additionalmethodological and applied readings.-- |
| Beschreibung: | 1 online resource. |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9781648028731 164802873X |
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| 245 | 0 | 0 | |a Multilevel modeling methods with introductory and advanced applications / |c Ann A. O'Connell, D. Betsy McCoach, Jeffrey R. Harring. |
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| 520 | |a 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 forinstructors, who must continually search for class examples and homeworkproblems. In addition, each chapter provides recommendations for additionalmethodological and applied readings.-- |c Provided by publisher. | ||
| 588 | |a Description based on online resource; title from digital title page (viewed on July 14, 2022). | ||
| 650 | 0 | |a Multilevel models (Statistics) |x Research. | |
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| author_additional | Ann. A O'Connell, D. Betsy McCoach, and Bethany A. Bell -- Bethany A. Bell and Jason A. Schoeneberger -- D. Betsy McCoach, Sarah D. Newton, Anthony J. Gambino -- Chris Rhoads and Eva Yujia Li -- Jessaca Spybrook, Benjamin M. Kelcey, and Nianbo Dong -- Audrey J. Leroux and S. Natasha Beretvas -- Ann A. O'Connell, Meng-Ting Lo, Jessica Goldstein, H. Jane Rogers, and C.-Y. Joanne Peng -- Ann A. O'Connell, Nivedita Bhaktha, and Jing Zhang -- D. Betsy McCoach, Bethany A. Bell, and Aarti P. Bellara -- Jeffrey R. Harring and Shelley A. Blozis -- Minjung Kim, Hsien-Yuan Hsu, and Oi-man Kwok -- Donald Hedeker and Robin J. Mermelstein -- Laura M. Stapleton and Scott L. Thomas -- Brian F. French, W. Holmes Finch, and Thao Vo -- Craig K. Enders and Timothy Hayes -- Nicholas J. Rockwood and Andrew F. Hayes -- John M. Ferron, Yan Wang, Zhiyao Yi, Yue Yin, Eunsook Kim, and Robert F. Dedrick. |
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| contents | Introduction to multilevel modeling methods: pedagogy and context / Organizational Data -- Introduction to multilevel models for organizational data / Evaluation of model fit and adequacy / Causal inference in multilevel settings / Statistical power for linear multilevel models / Cross-classified random-effects models / Multilevel logistic and ordinal models / Single and multilevel models for counts / Longitudinal Data -- Individual growth curve models for longitudinal data / Modeling nonlinear longitudinal change with mixed effects models / Within-subject residual variance-covariance structures in longitudinal data analysis / Modeling variation in intensive longitudinal data / Design and Special Issues -- Using large-scale complex sample datasets in multilevel modeling / Common measurement issues in a multilevel framework / Missing data handling for multilevel data / Multilevel mediation analysis / Reporting results of multilevel designs / |
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| discipline | Mathematik |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-11-27T13:30:34Z |
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| isbn | 9781648028731 164802873X |
| language | English |
| lccn | 2022004080 |
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| series | Quantitative methods in education and the behavioral sciences. |
| series2 | Quantitative Methods in Education and the Behavioral Sciences |
| spelling | Multilevel modeling methods with introductory and advanced applications / Ann A. O'Connell, D. Betsy McCoach, Jeffrey R. Harring. Charlotte, NC : IAP/Information Age Publishing, Incorporated, 2022. 1 online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier data file rda Quantitative Methods in Education and the Behavioral Sciences Includes bibliographical references. 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. 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 forinstructors, who must continually search for class examples and homeworkproblems. In addition, each chapter provides recommendations for additionalmethodological and applied readings.-- Provided by publisher. Description based on online resource; title from digital title page (viewed on July 14, 2022). Multilevel models (Statistics) Research. Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Modèles multiniveaux (Statistique) Recherche. Recherche quantitative. Quantitative research fast O'Connell, Ann A., editor. http://id.loc.gov/authorities/names/n2005033472 McCoach, D. Betsy, editor. http://id.loc.gov/authorities/names/n2008002151 Harring, Jeffrey, 1964- other. http://id.loc.gov/authorities/names/n2010083368 ProQuest (Firm) http://id.loc.gov/authorities/names/n2007068018 Print version: O'Connell, Ann A. Multilevel Modeling Methods with Introductory and Advanced Applications Charlotte, NC : Information Age Publishing, Incorporated,c2022 9781648028717 Quantitative methods in education and the behavioral sciences. http://id.loc.gov/authorities/names/n2005092606 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3186288 Volltext |
| spellingShingle | Multilevel modeling methods with introductory and advanced applications / Quantitative methods in education and the behavioral sciences. Introduction to multilevel modeling methods: pedagogy and context / Organizational Data -- Introduction to multilevel models for organizational data / Evaluation of model fit and adequacy / Causal inference in multilevel settings / Statistical power for linear multilevel models / Cross-classified random-effects models / Multilevel logistic and ordinal models / Single and multilevel models for counts / Longitudinal Data -- Individual growth curve models for longitudinal data / Modeling nonlinear longitudinal change with mixed effects models / Within-subject residual variance-covariance structures in longitudinal data analysis / Modeling variation in intensive longitudinal data / Design and Special Issues -- Using large-scale complex sample datasets in multilevel modeling / Common measurement issues in a multilevel framework / Missing data handling for multilevel data / Multilevel mediation analysis / Reporting results of multilevel designs / Multilevel models (Statistics) Research. Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Modèles multiniveaux (Statistique) Recherche. Recherche quantitative. Quantitative research fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2007000909 |
| title | Multilevel modeling methods with introductory and advanced applications / |
| title_alt | Introduction to multilevel modeling methods: pedagogy and context / Organizational Data -- Introduction to multilevel models for organizational data / Evaluation of model fit and adequacy / Causal inference in multilevel settings / Statistical power for linear multilevel models / Cross-classified random-effects models / Multilevel logistic and ordinal models / Single and multilevel models for counts / Longitudinal Data -- Individual growth curve models for longitudinal data / Modeling nonlinear longitudinal change with mixed effects models / Within-subject residual variance-covariance structures in longitudinal data analysis / Modeling variation in intensive longitudinal data / Design and Special Issues -- Using large-scale complex sample datasets in multilevel modeling / Common measurement issues in a multilevel framework / Missing data handling for multilevel data / Multilevel mediation analysis / Reporting results of multilevel designs / |
| title_auth | Multilevel modeling methods with introductory and advanced applications / |
| title_exact_search | Multilevel modeling methods with introductory and advanced applications / |
| title_full | Multilevel modeling methods with introductory and advanced applications / Ann A. O'Connell, D. Betsy McCoach, Jeffrey R. Harring. |
| title_fullStr | Multilevel modeling methods with introductory and advanced applications / Ann A. O'Connell, D. Betsy McCoach, Jeffrey R. Harring. |
| title_full_unstemmed | Multilevel modeling methods with introductory and advanced applications / Ann A. O'Connell, D. Betsy McCoach, Jeffrey R. Harring. |
| title_short | Multilevel modeling methods with introductory and advanced applications / |
| title_sort | multilevel modeling methods with introductory and advanced applications |
| topic | Multilevel models (Statistics) Research. Quantitative research. http://id.loc.gov/authorities/subjects/sh2007000909 Modèles multiniveaux (Statistique) Recherche. Recherche quantitative. Quantitative research fast |
| topic_facet | Multilevel models (Statistics) Research. Quantitative research. Modèles multiniveaux (Statistique) Recherche. Recherche quantitative. Quantitative research |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=3186288 |
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