
Applied Survey Data Analysis
Description
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New to the Third Edition:
Applied Bayesian methods for the analysis of complex sample survey data using available software implementing these methods
State-of-the-art methods and software for the analysis of survey data collected from non-probability samples
Software for modern applications of machine learning techniques to complex sample survey data
A completely revamped website providing code for replicating all the analyses illustrated in the book using Stata, SAS, SPSS, R, Mplus, SUDAAN, WesVar, and IVEware
New end-of-chapter exercises, allowing for practice implementing the methods, including Bayesian analysis exercises
Updated summaries of the newest literature on the analysis of survey data collected from complex samples
An updated review of software packages currently available for the analysis of complex sample survey data
Designed for readers working in a wide array of disciplines who conduct secondary analyses of survey data as part of their applied work, this book continues to provide a practical and accessible guide to the analysis of survey data. Continuing to use an example-driven approach to clearly illustrate analysis methods and software, the third edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also offer the newest code for replicating the examples in other popular software packages on the book's revamped website.
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Persons
Steven G. Heeringa is a Research Scientist Emeritus at the University of Michigan Institute for Social Research (ISR) and former Associate Director of the ISR Survey Research Center (SRC). He is a member of the faculty of the University of Michigan's Program in Survey and Data Science and the Joint Program in Survey Methodology. He is a Fellow of the American Statistical Association and elected member of the International Statistical Institute. He is the author of many publications on statistical design and sampling methods for research in the fields of public health and the social sciences. Steve has over 48 years of statistical sampling experience in the development of the SRC National Sample design, as well as research designs for ISR's major longitudinal and cross-sectional survey programs. Steve has collaborated extensively with scientific colleagues in the design and conduct of major studies in aging, psychiatric epidemiology and physical and mental health. He has been a teacher of survey sampling and statistical methods to U.S. and international students and has served as a sample design consultant to a wide variety of international research programs based in countries such as Russia, the Ukraine, Uzbekistan, Kazakhstan, India, Nepal, China, Egypt, Iran, the United Arab Emirates, Qatar, South Africa and Chile.
Patricia A. Berglund is a semi-retired Senior Research Associate in the Survey Methodology Program at the Institute for Social Research. She has extensive experience in the use of computing systems for data management and analysis of complex sample survey data. She works on research projects focused on paediatric health, youth substance abuse, adult mental health, and survey methodology using data from Pediatrac, Monitoring the Future, the National Comorbidity Surveys, and various other national and international surveys. In addition, she has been involved in development and teaching of analysis courses and computer training programs at the UM Survey Research Center-Institute for Social Research and previously lectured in the SAS Institute-Business Knowledge Series.
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