- Tapa blanda: 88 páginas
- Editor: SAGE Publications, Inc; Edición: 1 (8 de julio de 2004)
- Colección: Quantitative Applications in the Social Sciences
- Idioma: Inglés
- ISBN-10: 0761928790
- ISBN-13: 978-0761928799
- Valoración media de los clientes: Sé el primero en opinar sobre este producto
- Clasificación en los más vendidos de Amazon: nº450.521 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
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Multilevel Modeling (Quantitative Applications in the Social Sciences) (Inglés) Tapa blanda – 8 jul 2004
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Reseña del editor
Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.
Biografía del autor
Douglas A. Luke is currently a Professor at Washington University, George Warren Brown School of Social Work. He directs the Center for Tobacco Policy Research, has led the doctoral program at St. Louis University School of Public Health, and has long served on the key community health behavior study decision at the National Institute of Health.
In 1990 he received his Ph.D. in clinical/community psychology with a minor in quantitative psychology from the University of Illinois. While at the University of Illinois, he studied under a number or notable quantitative scientists and authors, including Phipps Arabie (co-author of Three-way Scaling & Clustering), Stanley Wasserman (editor of Advances in Social Network Analysis), Larry Jones, Larry Hubert, and Ledyard Tucker. His 1991 article, Expanding Behavior Setting Theory: Setting Phenotypes in a Mutual Help Organization, was recently selected as one of the ten most influential methodology articles published in the first 25 years of the American Journal of Psychology.
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In the end, don't bother with this book. The university of Bristol has an open course with just as good explanations, and full code in R, Stata, and HLM. Just search LEMMA Multilevel in Google.
Though most analysts are primarily interested in fixed effects, which makes perfect sense, interpretation of random effects can be instructive. Thanks to Luke's examples, random effects make a good deal more sense after reading his book. It's to his credit that he accomplishes this in an informal, almost off-handed way. Luke is not the sort of author who takes himself or his subject too seriously -- nothing deadeningly grave here -- and his presentation benefits from his relaxed approach.
Even if a reader is benefiting from one of the much longer texts that are currently available, this inexpensive little book is worth buying and looking over. Luke has the gift of succinctness -- saying a great deal with unusual clarity while using remarkably few words -- making his book a pleasure to read. If you've been away from multilevel analysis for awhile and are just getting back into, Luke's presentation will provide a fine review.