Free Kindle Applied Choice Analysis ebooks Download
The second edition of this popular book brings students fully up to date with the latest methods and techniques in choice analysis. Comprehensive yet accessible, it offers a unique introduction to anyone interested in understanding how to model and forecast the range of choices made by individuals and groups. In addition to a complete rewrite of several chapters, new topics covered include ordered choice, scaled MNL, generalized mixed logit, latent class models, group decision making, heuristics and attribute processing strategies, expected utility theory, and prospect theoretic applications. Many additional case studies are used to illustrate the applications of choice analysis with extensive command syntax provided for all Nlogit applications and datasets available online. With its unique blend of theory, estimation, and application, this book has broad appeal to all those interested in choice modeling methods and will be a valuable resource for students as well as researchers, professionals, and consultants.
Paperback: 1216 pages
Publisher: Cambridge University Press; 2 edition (August 4, 2015)
Language: English
ISBN-10: 1107465923
ISBN-13: 978-1107465923
Product Dimensions: 6.8 x 2 x 9.7 inches
Shipping Weight: 5.2 pounds (View shipping rates and policies)
Average Customer Review: 3.8 out of 5 stars See all reviews (6 customer reviews)
Best Sellers Rank: #886,267 in Books (See Top 100 in Books) #392 in Books > Business & Money > Economics > Econometrics #2286 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics #3334 in Books > Science & Math > Mathematics > Applied > Probability & Statistics
The whole book serves as a software (NLogit) manual. If you already know about the discrete choice analysis, you might be able to find out the messages that the authors try to convey. And it contains barely new information, so it doesn't help you anyway. But if you are new to this area, this is not the good book for you to start.The book is extremely verbose and the ideas are hidden behind lines and ill-presented. It turned out that it's very difficult to comprehend the essence or even sense of the choice methods from this book. The best one can get is becoming a software user of the authors' own program.Besides, the software, Nlogit, is not user-friendly and can't serve as a mainsteam tool.
This book is much more of a "how to" than a "theory of" text, which is excellent when you understand the theory but struggle with the actual mechanics. The book is based on the NLOGIT software, and is a much better manual for the software than what comes with the actual program. It links the theory with the commands to estimate the model, and how to interpret the model outputs. This is essential reading for anyone getting started in actual choice analysis.
This book is massive, and hence the term "primer" may be a little misleading. But if you really want to understand how to model choice data for a range of models, the book is outstanding. Other books focus more on the econometrics of the models, which are pivotal to know. But this book builds upon that by walking you through a series of increasingly-complex models, allowing you to understand why you need to perform particular modeling tasks.The book focuses on NLogit software, but once you understand how to actually estimate choice models utilizing software, the skills can be easily carried into other software programs. However, without such experience, the other books available may fall short in enabling you to estimate choice models. Indeed, this was the case for me -- I understood the econometrics of the models, but had difficulty estimating complex models using software, simply beacuse I was uncomfortable with the syntax.Hensher et al. removes this obstacle by giving the reader thorough training in both understanding what a given set of choice data may represent (e.g., observations from a particular choice experiment), and how to physically estimate models. The increase in confidence I received from working through the exercises in the book is why I rate the book so highly. Not only are the econometric concepts explained, but the nuts and bolts of model estimation are revealed, and that made all the difference.
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