Multilevel Modeling (Quantitative Applications in the Social Sciences),   ISBN:9780761928799

Customer Rating: 

Sage university papers on quantitative applications are presented as brief and inexpensive treatments of specialized topics in statistics and data analysis. Some are well worth the price, while some leave you wishing you used the money towards acquiring a full-length treatise or textbook. If you need to learn about multilevel modeling on your own, Douglas Luke's Multilevel Modeling is worth much more than its price, especially if you buy it from Amazon.com, because it is a model of compositional economy in addressing a complex idea, and of what a truly introductory textbook should be. Luke maintains focus, precision, and masterful clarity in a fashion that is rarely encountered among books which claim to be "An Introduction to ... " a topic as specialized, intricate, and novel as is multilevel statistical modeling. Luke defines the terms more lucidly than some of the most popular full-sized books which aim to introduce multilevel analysis (and which still leave the reader mired in ambiguity). The author does not attempt to impart any gratuitous complexity to his exposition and manages to integrate textual clarity with statistical notation and equations, figures, and tables which are equally clear for someone who, while familiar with concepts beyond one-variable statistics and simple linear regression and ANOVA, has never studied or engaged in this type of data analysis or research design before. You may need to proceed to thicker treatises to make a thorough analysis and find out how to use your favorite software, but if you begin with one or more of those and find the topic still unclear in its elements - either the big picture or the basic details - you will find Luke's 78 pages (including reference to data online) enlightening.

Customer Rating: 

Given the brevity imposed by Sage's little, green paperbacks, Luke's book is remarkably informative. This is especially true of models with more than three levels. Though Luke devotes only four pages to these more complex models, his examples are among the best I've seen. They lend credibility to the oft-repeated, but sometimes hard to see judgment that three-level models are almost as easy to specify, estimate, and understand as two-level models.

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.

Customer Rating: 

Luke provides a very clear explication of how to conduct Multilevel Modeling with very nice examples.