基本説明
Provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms; SPSS, SAS, and HLM.
Full Description
Hierarchical Linear Modeling provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original "how-to" application articles following a standardized instructional format. The Guide portion consists of five chapters that provide an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The Applications portion consists of ten contributions in which authors provide step-by-step presentations of how HLM is implemented and reported for introductory to intermediate applications.
"The book covers the three most widely accessible statistical programs for multilevel modeling rather than just focusing on one. . . . 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." —Debbie L. Hahs-Vaughn, University of Central Florida
"The intelligent use of the examples helps explain both the conceptual framework of HLM and its basic individual applications."—Luis L. Cabo, Mercyhurst College
Contents
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
