Mixed-Mode Official Surveys: Design and Analysis (Chapman & Hall/CRC Statistics in the Social a...


Categories: , Tag: GTIN: 9781138618459
Mixed-Mode Official Surveys: Design and Analysis
(Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
Size: 13 MB (13564434 bytes) Extension: pdf
Author(s): Barry Schouten, Jan van den Brakel, Bart Buelens, Deirdre Giesen, Annemieke Luiten, Vivian Meertens

Publisher: Chapman and Hall/CRC, Year: 2021

ISBN: 1138618454,9781138618459

Mixed-mode surveys have become a standard at many statistical institutes. However, the introduction of multiple modes in one design goes with challenges to both methodology and logistics. Mode-specific representation and measurement differences become explicit and demand for solutions in data collection design, questionnaire design, and estimation. This is especially true when surveys are repeated and are input to long time series of official statistics. So how can statistical institutes deal with such changes? What are the origins of mode-specific error? And how can they be dealt with? In this book, the authors provide answers to these questions, and much more.



  • Concise introduction to all the key elements of mixed-mode survey design and analyze
  • Realistic official statistics examples from three general population surveys
  • Suitable for survey managers and survey statisticians alike
  • An overview of mode-specific representation and measurement errors and how to avoid, reduce and adjust them
Table of contents :
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Part I Introduction
Chapter 1 Foreword to Mixed-Mode Official Surveys: Design and Analysis
1.1 Why a Book on Mixed-Mode Survey Design and Analysis?
1.2 Modes and Devices
1.3 Outline of the Book
Chapter 2 Designing Mixed-Mode Surveys
2.1 Introduction
2.2 Why Mixed-Mode Survey Designs?
2.3 How Can Modes Be Combined?
2.4 How Do Modes Affect Quality?
2.5 How to Reduce Mode Impact on Quality?
2.6 Case Studies
2.6.1 Dutch Crime Victimization Survey
2.6.2 Dutch Labour Force Survey
2.6.3 European Health Interview Survey
2.7 Summary
Part II Mode Effects
Chapter 3 Mode-Specific Measurement Effects
3.1 Introduction
3.2 Measurement Features of Modes
3.3 Mode-Specific Answering Behaviors and Response Styles
3.4 Detection of Mode-Specific Measurement Effects
3.5 Summary
Chapter 4 Mode-Specific Selection Effects
4.1 Introduction
4.2 Coverage Issues in CAPI, CATI, Mail, and Web Surveys
4.2.1 CAPI Coverage
4.2.2 CATI Coverage
4.2.3 Mail Coverage
4.2.4 Web Coverage
4.3 Response and Subgroup Response Rates in Mixed-Mode Designs
4.3.1 Mixed-Mode Designs at Statistics Netherlands
4.4 Summary
Part III Design
Chapter 5 Mixed-Mode Data Collection Design
5.1 Introduction
5.2 Mode and Mode Combinations
5.3 Concurrent and Sequential Designs
5.3.1 Concurrent or Sequential Order?
5.3.2 Sequential, but Which Sequence?
5.4 Costs
5.5 Sample Composition and Data Quality
5.6 Communication Strategies to Increase Web Response
5.6.1 Contacting the Sample Person or Household
5.6.2 Reminders
5.6.3 Invitation Letters, Flyers, and Envelopes: Statistics Netherlands’ Experiments Experimental Manipulations Results
5.6.4 Incentives in Web and Mixed-Mode Surveys Effect on Sample Composition and Data Quality Incentives in European NSIs Incentive Experiments by Statistics Netherlands An Incentive Experiment in the Longitudinal Labor Force Survey2
5.7 Summary
Chapter 6 Mixed-Mode Questionnaire Design
6.1 Introduction
6.2 General Goals and Challenges in Questionnaire Design
6.2.1 Why Questionnaire Matters
6.2.2 Striking a Balance between Conflicting Goals and Stakeholders
Clients (Partly Overlap with Data Users)
Data Users (Partly Overlap with Clients)
Project Managers
Questionnaire Designers
6.2.3 Questionnaire Design as an Iterative Process
6.3 Questionnaire Design and Mode-Specific Measurement Errors
6.3.1 The Cognitive Response Process Model
6.3.2 Main Sources of Mode-Specific Measurement Error
6.3.3 Even Small Design Differences May Matter
6.3.4 Device-Specific Measurement Errors
6.4 Questionnaire Design for Mixed-Mode Surveys
6.4.1 Minimizing Differences or Minimizing Error?
6.4.2 Mixed-Mode Requirements in the Questionnaire Design Process
6.4.3 Mixed-Device Questionnaire Design
6.5 Testing and Evaluating Mixed-Mode Questionnaires
6.5.1 Testing and Evaluation as Part of the Questionnaire Design Process
6.5.2 Mixed-Mode Questionnaire Testing and Evaluation
Step 1 Make an Explicit Mode Risk Assessment
Step 2 Decide if the Test Should Compare Modes
Step 3 Decide Which Modes to Test, and When in the Development Process
Step 4 Test Relevant Modes as Realistically as Practically Possible
Step 5 In Analyses and Reporting, Distinguish between Usability and Content Findings, and Reflect on Mode and Device Specificity Regarding Findings
6.6 Guidelines for Mixed-Mode Questionnaire Design
6.6.1 Keep the Stimulus and Response Task as Similar as Possible in All Modes
6.6.2 Organize the Questionnaire Design Process to Prevent and Detect Mode-Specific Measurement Errors
6.6.3 Prevent Social Desirability Bias
6.6.4 Prevent Satisficing
6.7 Summary
Part IV Analysis
Chapter 7 Field Tests and Implementation of Mixed-Mode Surveys
7.1 Introduction
7.2 Design of Field Experiments
7.3 Design-Based Inference for Field Experiments
7.3.1 Measurement Error Model and Hypotheses Testing
7.3.2 Parameter and Variance Estimation
7.3.3 Wald Test and Related Tests
7.3.4 Extensions
7.3.5 Software
7.4 Time Series Methods
7.5 Small Area Estimation Methods
7.6 The Introduction of a Hybrid Mixed-Mode Design in the Dutch Crime Victimization Survey
7.6.1 Design
7.6.2 Results
7.7 Discussion
7.8 Summary
Chapter 8 Re-interview Designs to Disentangle and Adjust for Mode Effects
8.1 Introduction
8.2 Decomposition of Relative Mode Effects
8.3 Estimating Components of the Relative Mode Effects
8.3.1 Experimental Design
8.3.2 Estimation Strategies
8.3.3 Assumptions
8.4 Application
8.5 Adjusting Measurement Bias Using Re-interview Designs
8.6 Simulation Study
8.7 Extension of Re-interview Design to Multiple Modes
8.8 Conclusions
8.9 Summary
Chapter 9 Mixed-Mode Data Analysis
9.1 Introduction
9.2 Analyzing Mixed-Mode Survey Response Data
9.2.1 Literature
9.2.2 Problem Statement, Definitions, and Notation
9.3 Correcting Differential Measurement Bias
9.3.1 Counterfactuals
9.3.2 Mode-Specific Estimators
9.4 Balancing Differential Measurement Bias
9.4.1 Mode Calibration
9.4.2 Choosing Calibration Levels
9.5 Handling Measurement Bias in Practice
9.5.1 Testing Assumptions
9.5.2 Calibration Levels and Mixing Coefficients
9.5.3 Comparison with Single-Mode Designs
9.6 Applications
9.6.1 Health Survey
9.6.2 Crime Victimization Survey
9.6.3 Labor Force Survey
9.7 Summary
Part V The Future of Mixed-Mode Surveys
Chapter 10 Multi-Device Surveys
10.1 Introduction
10.2 Smart Surveys
10.2.1 A Taxonomy of Smart Surveys
10.2.2 Sensor Data
10.2.3 Other Types of External Data
10.3 Total Survey Error
10.3.1 Representation and Measurement of Smart Surveys
10.3.2 Criteria to Include New Types of Data
10.4 Methodology for Hybrid Data Collection
10.4.1 Active Versus Passive Data Collection
10.4.2 Data Collection Strategies
10.4.3 Measurement Strategies
10.4.4 Estimation Strategies
10.4.5 Logistics and Operations
10.5 Case Studies
10.5.1 Smart Survey Criteria
10.5.2 A Case Study Elaborated: Physical Activity
10.6 Summary
Chapter 11 Adaptive Mixed-Mode Survey Designs
11.1 Introduction
11.2 Elements of Adaptive Multi-Mode Survey Designs
11.2.1 Survey Mode as a Design Feature
11.2.2 Population Strata
11.2.3 Quality and Cost Objectives in Multi-Mode Surveys
11.2.4 Optimization Strategies
11.3 Case Studies
11.3.1 The Dutch LFS
11.3.2 The Dutch HS
11.4 Summary
Chapter 12 The Future of Mixed-Mode Surveys
12.1 Introduction
12.2 What Are the Current Developments?
12.3 What Are the Open Areas in the Methodology of Mixed-Mode Surveys
12.4 Open Areas in Logistics and Implementation of Mixed-Mode Surveys
12.5 Will There Be Mixed-Mode Surveys in the Future?

Stay Connected

We don’t spam! Read our privacy policy for more info.

Shopping Cart