Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members. What are current best practices in ASD? Is ASD worthwhile when the same auxiliary data are employed in the estimation afterwards? In this book, the authors provide answers to these questions, and much more.
Andy Peytchev is a research assistant professor in the University of Michigan's Program in Survey Methodology and the Joint Program in Survey Methodology at the University of Maryland.
Barry Schouten is senior methodologist at Statistics Netherlands and professor at Utrecht University.
James Wagner is research associate professor in the University of Michigan's Program in Survey Methodology and the Joint Program in Survey Methodology at the University of Maryland.
Part I: Introduction to Adaptive Survey Design
Introduction to the Handbook
What is an Adaptive Survey Design?
Part II: Preparing an Adaptive Survey Design
Stratification
Strategies and Interventions
Modelling and Monitoring Nonresponse
Part III: Implementing an Adaptive Survey Design
Costs and Logistics
Optimization of an Adaptive Survey Design
Sensitivity Analyses
Part IV: Advanced Features of Adaptive Survey Design
Indicators to Support Optimization and Prioritization
Adaptive Survey Design and Adjustment for Nonresponse
Part V: The Future of Adaptive Survey Design
Adaptive Survey Design and Measurement Error
The Future of Adaptive Survey Design