Mixed-Mode Official Surveys: Design and Analysis
(Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
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| 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 Description:
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. Features
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| Table of contents : Cover Half Title Series Page Title Page Copyright Page Table of Contents Preface Acknowledgements Authors 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 Notes 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 5.6.3.1 Experimental Manipulations 5.6.3.2 Results 5.6.4 Incentives in Web and Mixed-Mode Surveys 5.6.4.1 Effect on Sample Composition and Data Quality 5.6.4.2 Incentives in European NSIs 5.6.4.3 Incentive Experiments by Statistics Netherlands 5.6.4.4 An Incentive Experiment in the Longitudinal Labor Force Survey2 5.7 Summary Notes 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) Respondents Interviewers Programmers 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 Note 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? References Index |
