Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data.It emphasizes methods and worked examples using available software procedures while reinforcing the principles and theory that underlie those methods.After introducing a step-by-step process for approaching a survey analysis problem, the book presents the fundamental features of complex sample designs and shows how to integrate design characteristics into the statistical methods and software for survey estimation and inference.The authors then focus on the methods and models used in analyzing continuous, categorical, and count-dependent variables; event history; and missing data problems.Some of the techniques discussed include univariate descriptive and simple bivariate analyses, the linear regression model, generalized linear regression modeling methods, the Cox proportional hazards model, discrete time models, and the multiple imputation analysis method.The final chapter covers new developments in survey applications of advanced statistical techniques, including model-based analysis approaches.Designed for readers working in a wide array of disciplines who use survey data in their work, this book also provides a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis.A guide to the applied statistical analysis and interpretation of survey data, it contains many examples and practical exercises based on major real-world survey data sets.Although the authors use Stata for most examples in the text, they offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s website: http://www.isr.umich.edu/src/smp/asda/
Amazon Sales Rank: #193878 in Books Published on: 2010-04-05 Original language: English Number of items: 1 Binding: Hardcover 487 pages
Review 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 a*sistant 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 a*sociate 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.
The best customer feedback 3 of 3 people found the following review helpful.Just a great book by Dennis Hanseman Applied Research Data Analysis (ASDA) is a survey course of modern techniques for analyzing complex survey data.Notice the word "analysis".This is not a text on methods of sampling itself.Rather, it is a guide to using existing data derived from a research project using a complex weighting, clustering, and stratification.The authors show how a good analysis should be conducted.Thus, a review of descriptive statistics, categorical methods, regression analysis (linear and logistic regression), survival analysis and multiple imputation.Most examples use Stata, but some are in SAS.The level of mathematical sophistication is not high, but "the theory of boxes" are interspersed to add details.Anyone who is questioned by the level of math in this book, you probably should not be working with survey data in the first place.In short, this is an important - contribution to the literature on the analysis of survey data 0 of 0 people found the following review helpful - and very well written.A must-have for any analysis of the survey by Kristen Olson This book is unique in the market for books on extensive analysis of survey data.Most of the data collected in finite populations were selected with unequal chances of selection, layers and groups, but most textbooks regression a*sumes a simple random sample.This is the first full-length book about subcla*s analysis, categorical data analysis, and various generalized linear models (linear regression with hierarchical models) and complex statistical research projects at a level accessible to most students graduate or data analysts.Creation of weights and multiple imputation are also covered.Readers not put off by "many" formulas in this book.Although the formulas used throughout the book is a great amount of detail presenteres statistical theory, moreover, the "Theory boxes' provide sufficient data to statistically inclined readers know who to contact for more information This book is best for a more sophisticated statistical models of cla*s when students have taken their basic regression / correlation cla*s (and eventually, after a cla*s of categorical data).The homework at the end of each chapter is a useful adjunct to the text, with the necessary data sets available on the website for the book.I find that homework a*signments are integrated with further examples with other datasets, especially for cla*ses taught several times, but they are a good starting point.I recommend this book to anyone who wants a "how to" book for analysis and interpretation of complex data, supplemented by extensive documentation about the model fit and the diagnosis of a complex survey design (if available) immediately useful for the Stata code for all the analysis in the text and the code for SAS, Stata, Mplus, R, SUDAAN, and SPSS WesVar on the website.See all 2 reviews ....
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