Table of Contents

Preface

Applied Survey Data Analysis: An Overview

Getting to Know the Complex Sample Design

Foundations and Techniques for Design-based Estimation and Inference

Preparation for Complex Sample Survey Data Analysis

Descriptive Analysis for Continuous Variables

Categorical Data Analysis

Linear Regression Models

Logistic Regression and Generalized Linear Models for Binary Survey Variables

Generalized Linear Models for Multinomial, Ordinal and Count Variables

Survival Analysis of Event History Survey Data

Analysis of Longitudinal Complex Sample Survey Data

Imputation of Missing Data: Practical Methods and Applications for Survey Analysts

Advanced Topics in the Analysis of Survey Data

Appendix A: Software Overview

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 Research Associate Professor in the Survey Research Center at the University of Michigan’s Institute for Social Research. He is also a statistical consultant on the Consulting for Statistics, Computing, and Analytics Research (CSCAR) team at the University of Michigan.

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.

Reviews

"Anyone analyzing survey data, even once, should have a copy of this book. The book has something for everyone. It is a solid, yet accessible introduction to analyzing data from complex sample surveys (i.e., those with stratification and clustering), a statistical text of the highest caliber, and a reference for experienced analysts and statisticians. The authors are masterful instructors on the topic, and leaders in the field of survey methodology at the University of Michigan's world-renowned Institute for Social Research and Survey Research Center. Their profound understanding of the topic, and talent for describing it shines through vividly in the text. One of my favorite parts remains section 1.2 "A Brief History of Applied Survey Data Analysis", which is split into "Key Theoretical Developments" and "Key Software Developments". The historical context provided in those sections helps motivate the technical material that follows. My other favorite parts of this book are the presentations of analysis code and output from various programs, and their "Theory Boxes", which tie specific analysis steps and code to the statistical theory behind them. Among the numerous updates to this edition, I think readers will find the new content on model diagnostics and testing goodness-of-fit (GOF) to be extremely helpful, as this is an area of complex sample survey analysis that can be difficult to translate from standard regression analysis. Throughout, the authors make it a point to describe analyses in discrete steps that can help direct even the most complex analyses."
—Matt Jans, Senior Associate/Scientist, Abt Associates "This is an excellent book to use for a graduate level applied statistics course teaching public health students how to analyze complex survey data. Each chapter is clearly written with a nice balance of theoretical background and practical guidance on survey data analytical issues as illustrated by many relevant real-data examples.