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Product details
File Size: 3968 KB
Print Length: 162 pages
Publisher: Oxford University Press; 1 edition (July 25, 2008)
Publication Date: July 25, 2008
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B001UV3BXQ
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Amazon Best Sellers Rank:
#1,724,588 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
The Preface to this book says that "... a basic understanding of epidemiology and statistics is assumed." If you think that basis statistics = a one year course, you would be quite wrong. Just looking at the beginning of the book's index, you would find: additive logistic model, Akaike's information criterion, autoregressive model, Breusch-Pagan test, discriminant analysis, empirical Bayes, and Fourier processing. None of these concepts is explained.Amazon indicates that this book contains 209 pages. Readers should be aware, however, that there are only 119 pages of actual text. I was stunned when I received the book. After paying over $40, it seemed overly expensive.These caveats aside, the book is pretty well written, although with a skew toward veterinary rather than human epidemiological concens.
A very good book and very easy to read. It is a good introduction to spatial analysis, statistic is exhaustive although somewhat superficial, and the examples are good. Black and white maps are a problem during reading, although this was solved with the same maps in color in the middle of the book. I am interested in the spatial analisis of the diagnostic lab data and the book has been a good help.
Pretty good so far. It's good for mathematical lay people like me
THIS BOOK HAS OPENED MY MIND TO A NEW AND BETTER WAY OF ANALYZING MASSIVE DATA ON HEALTH ISSUES AND SPACE. IT SHOWS HOW MUCH GIS CAN DO FOR HEALTH SCIENCE AS WELL AS WHAT IT CANNOT DO. HEALTH PLANNERS WILL FIND THE METHODOLOGIES PRESENTED IN THIS BOOK THE BEST SHORTCUT FOR MAKING CONCLUSIONS ON THE RELATIOSHIPS BETWEEN ENVIRONMENT AND HEALTH IN A GIVEN PLACE.
This book includes more types of spatial analyses than I have previously seen under one roof, so to speak. However, it does not cover any analyses in detail, nor does it provide any worked examples! As a consequence, this book is not appropriate for those who are new to spatial stats or who need some practical experience with them. For practitioners who are already familiar with basic spatial analyses (e.g. Moran's I, semivariance), then the book offers some related methods and does a nice job of concisely summarizing and comparing different tests.
This book is a great start to the topic of spatial epidemiology. We read it as a required text for a Masters in Epi Geospatial Epidemiology course. The first couple of chapters are great, but the statistical definitions of some concepts are too vague for a researcher learning to apply new methods.
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