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