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Hierarchical Linear Modeling: Guide and Applications de George David Garson

Hierarchical Linear Modeling: Guide and Applications

Editat de George David Garson
en Limba Engleză Electronic book text – 18 iun 2013
This book provides a brief, easy-to-read guide to implementing hierarchical linear modelling using the three leading software platforms, followed by a set of application articles based on recent work published in leading journals and as part of doctoral dissertations. The "guide" portion consists of three chapters by the editor, covering basic to intermediate use of SPSS, SAS, and HLM for purposes for hierarchical linear modelling, while the "applications" portion consists of a dozen contributions in which the authors emphasize how-to and methodological aspects and show how they have used these techniques in practice.
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Specificații

ISBN-13: 9781452280981
ISBN-10: 1452280983
Pagini: 392
Dimensiuni: 187 x 232 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States

Recenzii

"The book covers the three most widely accessible statistical programs for multilevel modeling rather than just focusing on one. It will be an excellent tool for researchers who are beginning to learn multilevel modeling as well as a great resource for experienced researchers who want to learn a different statistical program for multilevel models.”
“This books covers the usage and outputs of the three main statistical packages for the application of HLM, and the intelligent use of the examples help explain both the conceptual framework of HLM and its basic individual applications.”

Cuprins

Chapter 1. Fundamentals of Hierarchical Linear (Multilevel) Modeling - G. David Garson
Chapter 2. Preparing to Analyze Multilevel Data - G. David Garson
Chapter 3. Introductory Guide to HLM with HLM6 Software - G. David Garson
Chapter 4. Introductory Guide to HLM with SAS Software - G. David Garson
Chapter 5. Introductory Guide to HLM with SPSS Software - G. David Garson
Chapter 6. A Random Intercepts Model of GPA and SAT Scores Using SPSS - Forrest C. Lane, Kim F. Nimon & J. Kyle Roberts
Chapter 7. A Random Intercept Regression Model Using HLM: Cohort Analysis of a Mathematics Curriculum for Mathematically Promising Students - Carissa L. Shafto & Jill L. Adelson
Chapter 8. A Random Coefficients Model Using HLM: Studying the Achievement Gap in Schools - Gregory J. Palardy
Chapter 9. Emotional Reactivity to Daily Stressors Using a Random Coefficients Model with SAS Proc Mixed - Shevaun Neupert
Chapter 10. Hierarchical Linear Modeling of Growth Curve Trajectories Using HLM - David F. Greenberg & Julie A. Phillips
Chapter 11. A Piecewise Growth Model Using HLM to Examine Change in Teaching Practices Following a Science Teacher Professional Development Intervention - Jaime Lynn Maerten-Rivera
Chapter 12. Studying Reaction to Repeated Life Events with Discontinuous Change Models Using HLM - Maike Luhmann & Michael Eid
Chapter 13. A Cross-Classified Multilevel Model for First-Year College Natural Science Performance Using SAS - Brian F. Patterson
Chapter 14. Cross-Classified Multilevel Models Using STATA: How Important Are Schools and Neighborhoods for Children's Educational Attainment? - George Leckie
Chapter 15. Predicting Future Events from Longitudinal Data with Multivariate Hierarchical Models Using SAS - Larry J. Brant & Shan L. Sheng

Descriere

An introduction to the concepts, assumptions, and practical implementation procedures involved in common types of projects based on hierarchical linear modelling, multilevel modelling, or linear mixed modelling.