Site Overview
This site provides information about all editions of the textbook “Applied Survey Data Analysis”, including a Project Overview, Information about Authors, and Professional Reviews along with links to the following Resources:
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- Data Sets Used in Analysis Examples and Chapter Exercises
- Code and Output from Replication of Analysis Examples Using Current Software Packages (SAS, SPSS, R, Stata, IVEware, and MPlus). We highlight the Third Edition while the First and Second Editions Resources are Archived.
- Survey Data Analysis Publications
- FAQs and Supplemental Code Examples
- Public Release Data and Software Sites
- Additional Sites for Survey Data Analysis
- Errata
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Project Overview
Applied Survey Data Analysis is the product born of many years of teaching applied survey data analysis classes and practical experience analyzing survey data. We have taught various versions of this course in the ISR/SRC Summer Institute Program, as part of University of Michigan/CSCAR, and within the Program in Survey and Data Science at the University of Michigan (surveydatascience.isr.umich.edu) and the Joint Program in Survey Methodology at the University of Maryland (jpsm.umd.edu). Our goal has been to integrate teaching materials and practical analysis knowledge into a textbook geared to a level accessible for graduate students and working analysts who may have varying levels of statistical and analytic expertise. We intend to update the materials on this website as statistical and software improvements emerge with the goal of assisting analysts and researchers performing survey data analysis.
Resources for ASDA – Third Edition
Link to Book Page for Applied Survey Data Analysis, Third Edition
Link to Analysis Examples Replication in Multiple Software Packages, Third Edition
Link to Chapter Exercises and Analysis Examples Replication Data Sets, All Editions
Link to Survey Data Analysis Publications, Third Edition
Link to Supplemental Code Examples, All Editions
Link to Public Release Data Sets, All Editions
Link to Additional Sites and Software
Link to Statistical Resources
Link to Errata, Third Edition (Forthcoming)
Professional Reviews of ASDA – Third Edition
Reviews are forthcoming.
Information About Authors
Brady T. West is a Research Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research on the University of Michigan-Ann Arbor (U-M) campus. He earned his PhD from the Michigan Program in Survey and Data Science in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, selection bias in surveys, responsive/adaptive survey design, interviewer effects, and multilevel regression models for clustered and longitudinal data. An author or co-author of more than 200 peer-reviewed publications in survey statistics, applied statistics, and public health, he is also the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures (Linear Mixed Models: A Practical Guide using Statistical Software, Third Edition, Chapman Hall/CRC Press, 2022). He was elected as a Fellow of the American Statistical Association in 2022. Brady lives in Dexter, Michigan with his wife Laura, his son Carter, and his daughter Everleigh.
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.
Archived Resources for ASDA First and Second Editions
Link to Analysis Example Replication in Multiple Software Tools, Second Edition
Link to Analysis Example Replication in Multiple Software Tools, First Edition
Link to FAQ and Working Papers, First and Second Editions
Link to Errata, First and Second Editions
Please report problems or send comments via e-mail to pberg@umich.edu.