- Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences (Book 8)
- Hardcover: 487 pages
- Publisher: Chapman and Hall/CRC; 1 edition (April 5, 2010)
- Language: English
- ISBN-10: 1420080660
- ISBN-13: 978-1420080667
- Product Dimensions: 6.2 x 1.2 x 9.3 inches
- Shipping Weight: 1.8 pounds
- Average Customer Review: 5 customer reviews
- Amazon Best Sellers Rank: #221,173 in Books (See Top 100 in Books)
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Applied Survey Data Analysis (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) 1st Edition
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the authors do an admirable job of striking a balance between statistical theory and practical advice and analysis. The authors provide excellent coverage of each aspect of the survey analysis process … This book is an excellent general resource and if the reader is left wanting on a topic the authors never fail to provide an ample set of citations and references to a wide variety of notable texts on the topic in question. … an excellent and helpful addition to the desk of any analyst, researcher, or student with a general background in statistics who is dealing with the special challenges and demands of complex survey data.
―Gregory Holyk, Journal of Official Statistics, Vol. 27, 2011
Overall, the book is clearly written and easy to follow, and well equipped with real data examples and a book website. The program codes used in the example are also available, mostly written in Stata. I like the presentations with real survey examples and, in particular, the unified four-step approach to the regression analysis in different models. Anyone working on survey data analysis would find the book very helpful and instructive. The book website seems to be a good complement, with additional resources on this book.
―Jae-Kwang Kim, The American Statistician, November 2011
The book is well-written by authors who have over 60 years of combined teaching and consultation experience in survey methodology and research techniques. It is excellent for reference, with 12 structured chapters coherently organised, providing intermediate-level statistical overview of techniques used in analysing complex survey data. … It provides analysts with a framework of how to plan and conduct analysis of survey data, familiarise with terminologies used and understand common complex sample design features of clustering, stratification and weighting. … it is an excellent reference book for Stata users and the accompanying website provides useful resources and updated information. I feel that the book seamlessly links theory with practical applications of the statistical methods and helps the reader to develop an understanding of the framework of thinking required to effectively analyse complex survey data sets. …
―E.C. Abraham, AQMeNtion Newsletter, April 2011
… there is a wealth of instruction here. The writing style is expansive, keeping mathematics in check, and the material is well organized clearly into appropriate sections. I think that the book would serve any budding survey practitioner well: armed with the knowledge and practical skills covered herein, plus some real-life experience of course, one could reasonably claim to be well qualified in the subject.
―International Statistical Review (2010), 78, 3
About the Author
Steve G. Heeringa is a research scientist in the Survey Methodology Program, the director of the Statistical and Research Design Group in the Survey Research Center, and the director of the Summer Institute in Survey Research Techniques at the University of Michigan’s Institute for Social Research.
Brady T. West is a doctoral student and research assistant in the Survey Research Center at the University of Michigan’s Institute for Social Research. He is also a statistical consultant in the Center for Statistical Consultation and Research.
Patricia A. Berglund is a senior research associate in the Youth and Social Indicators Program and Survey Methodology Program in the Survey Research Center at the University of Michigan’s Institute for Social Research.
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Top customer reviews
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To give an idea of my background: My formal biostatistics training is quite limited to what I got through experience on different research projects and through medical school. I use Stata 12 in a very basic way, and this was the first project using a large dataset that I did my own analysis for from start to finish. I've worked with weighted survey data before, but another statistician was doing all the actual coding.
I thought this book was pretty balanced between theory and practical issues. A lot of the theory was over my head, but certain parts were extremely illuminating and useful to read through. They do specify at least two semester of graduate level statistics or something like that as a prerequisite, but obviously I don't have that and I still found the book useful. The real value of the book lies in its numerous and detailed examples. The authors actually use NHANES data (and other national datasets) to work through their examples. They walk you through many different types of analyses, include multiple linear regression, multiple logistic regression, etc. Many of these examples are very detailed, and they build the whole model step-by-step and explain the rationale behind each step and decision. The book is extremely well organized, so that by flipping through the table of contents you can immediately find the relevant section for what you want to do with the data, read through the example, and apply the Stata code directly to your own analysis.
NHANES does have tutorials about how to work through their data; although I also found those to be useful and essential, I think that this book is superior because it does give more background about why you need to run certain types of analyses and tests rather than others.
I can't believe my university library didn't have this book--I think it's a totally worthwhile purchase for anyone preparing to work with large national datasets.
The level of mathematical sophistication is not high, although "theory boxes" are interspersed to add additional detail. Anyone who is challenged by the mathematical level of this book probably should not be working with survey data in the first place.
In sum, this is an important -- and very well written -- contribution to the literature on survey data analysis.
Cannot really comment on their R code since I have not used it for that. (I do think conceptually it is much better than Lumley's book on complex survey analysis in R.)
Readers will not be scared off by 'too many' formulas in this book. Although formulas are used throughout the book, there is not a great deal of detailed statistical theory presented; additionally, the 'Theory Boxes' provide enough information for more statistically inclined readers to know where to turn for more information. The book is best used for a more advanced statistical models class, after students have taken their basic regression/correlation class (and possibly after a categorical data class). The homework assignments at the end of each chapter are a useful addition to the text, with the required data sets available on the book's website. I find that the homework assignments are best supplemented with additional examples with other data sets, especially for classes taught repeatedly, but they are a great starting place.
I strongly recommend this book to anyone wanting a 'how to' book for conducting and interpreting analyses on complex survey data, supplemented with extensive documentation on model fitting and diagnostics under a complex survey design (where they are available). It is immediately useful, with Stata code for all of the analyses provided in the text and SAS, Stata, MPlus, R, SUDAAN, WesVar, and SPSS code on the website.