Handbook of Web Surveys
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More About This Title Handbook of Web Surveys

English

BEST PRACTICES TO CREATE AND IMPLEMENTHIGHLY EFFECTIVE WEB SURVEYS

Exclusively combining design and sampling issues, Handbook of Web Surveys presents a theoretical yet practical approach to creating and conducting web surveys. From the history of web surveys to various modes of data collection to tips for detecting error, this book thoroughly introduces readers to the this cutting-edge technique and offers tips for creating successful web surveys.

The authors provide a history of web surveys and go on to explore the advantages and disadvantages of this mode of data collection. Common challenges involving under-coverage, self-selection, and measurement errors are discussed as well as topics including:

  • Sampling designs and estimation procedures

  • Comparing web surveys to face-to-face, telephone, and mail surveys

  • Errors in web surveys

  • Mixed-mode surveys

  • Weighting techniques including post-stratification, generalized regression estimation, and raking ratio estimation

  • Use of propensity scores to correct bias

  • Web panels

Real-world examples illustrate the discussed concepts, methods, and techniques, with related data freely available on the book's Website. Handbook of Web Surveys is an essential reference for researchers in the fields of government, business, economics, and the social sciences who utilize technology to gather, analyze, and draw results from data. It is also a suitable supplement for survey methods courses at the upper-undergraduate and graduate levels.

English

Jelke Bethlehem, PhD, is Senior Advisor in the Department of Statistical Methods at Statistics Netherlands and Professor of Statistical Information Processing at the University of Amsterdam. His current research interests include web surveys, computer-assisted survey information collection, graphical techniques in statistics, and user-friendly software for statistical analysis. He is coeditor of Computer Assisted Survey Information Collection, author of Applied Survey Methods: A Statistical Perspective, and coauthor of Handbook of Nonresponse in Household Surveys, all published by Wiley.

Silvia Biffignandi is Professor of Economic and Business Statistics and Director of the Centre for Statistical Analyses and Survey Interviewing (CASI) at the University of Bergamo (Italy). She currently focuses her research in the areas of web surveys, online panels, and official statistics.

English

PREFACE xi

1 THE ROAD TO WEB SURVEYS 1

1.1 Introduction, 1

1.2 Theory, 2

1.2.1 The Everlasting Demand for Statistical Information, 2

1.2.2 The Dawn of Sampling Theory, 4

1.2.3 Traditional Data Collection, 8

1.2.4 The Era of Computer-Assisted Interviewing, 10

1.2.5 The Conquest of the Web, 12

1.3 Application, 21

1.4 Summary, 31

2 ABOUT WEB SURVEYS 37

2.1 Introduction, 37

2.2 Theory, 40

2.2.1 Typical Survey Situations, 40

2.2.2 Why On-Line Data Collection?, 45

2.2.3 Areas of Application, 48

2.2.4 Trends in Web Surveys, 50

2.3 Application, 52

2.4 Summary, 55

3 SAMPLING FOR WEB SURVEYS 59

3.1 Introduction, 59

3.2 Theory, 60

3.2.1 Target Population, 60

3.2.2 Sampling Frames, 63

3.2.3 Basic Concepts of Sampling, 68

3.2.4 Simple Random Sampling, 71

3.2.5 Determining the Sample Size, 74

3.2.6 Some Other Sampling Designs, 76

3.2.7 Estimation Procedures, 82

3.3 Application, 87

3.4 Summary, 92

4 ERRORS IN WEB SURVEYS 97

4.1 Introduction, 97

4.2 Theory, 103

4.2.1 Measurement Errors, 103

4.2.2 Nonresponse, 124

4.3 Application, 133

4.3.1 The Safety Monitor, 133

4.3.2 Measurement Errors, 134

4.3.3 Nonresponse, 136

4.4 Summary, 138

5 WEB SURVEYS AND OTHER MODES OF DATA COLLECTION 147

5.1 Introduction, 147

5.1.1 Modes of Data Collection, 147

5.1.2 The Choice of the Modes of Data Collection, 149

5.2 Theory, 152

5.2.1 Face-To-Face Surveys, 152

5.2.2 Telephone surveys, 158

5.2.3 Mail Surveys, 164

5.2.4 Web surveys, 169

5.3 Application, 174

5.4 Summary, 182

6 DESIGNING A WEB SURVEY QUESTIONNAIRE 189

6.1 Introduction, 189

6.2 Theory, 191

6.2.1 The Road Map Toward a Web Questionnaire, 191

6.2.2 The Language of Questions, 197

6.2.3 Answers Types (Response Format), 200

6.2.4 Basic Concepts of Visualization, 211

6.2.5 Web Questionnaires and Paradata, 217

6.2.6 Trends in Web Questionnaire Design and Visualization, 223

6.3 Application, 226

6.4 Summary, 228

7 MIXED-MODE SURVEYS 235

7.1 Introduction, 235

7.2 Theory, 238

7.2.1 What is Mixed Mode?, 238

7.2.2 Why Mixed Mode?, 243

7.2.3 Methodological Issues, 248

7.2.4 Mixed Mode for Business Surveys, 262

7.2.5 Mixed Mode for Surveys Among Households and Individuals, 267

7.3 Application, 272

7.4 Summary, 274

8 THE PROBLEM OF UNDERCOVERAGE 281

8.1 Introduction, 281

8.2 Theory, 287

8.2.1 The Internet Population, 287

8.2.2 A Random Sample From the Internet Population, 288

8.2.3 Reducing the Noncoverage Bias, 290

8.2.4 Mixed-Mode Data Collection, 294

8.3 Application, 295

8.4 Summary, 299

9 THE PROBLEM OF SELF-SELECTION 303

9.1 Introduction, 303

9.2 Theory, 306

9.2.1 Basic Sampling Theory, 306

9.2.2 A Self-Selection Sample fromthe Internet Population, 309

9.2.3 Reducing the Self-Selection Bias, 314

9.3 Application, 319

9.4 Summary, 323

10 WEIGHTING ADJUSTMENT TECHNIQUES 329

10.1 Introduction, 329

10.2 Theory, 334

10.2.1 The Concept of Representativity, 334

10.2.2 Poststratification, 336

10.2.3 Generalized Regression Estimation, 349

10.2.4 Raking Ratio Estimation, 358

10.2.5 Calibration Estimation, 361

10.2.6 Constraining the Values of Weights, 362

10.2.7 Correction Using a Reference Survey, 363

10.3 Application, 372

10.4 Summary, 378

11 USE OF RESPONSE PROPENSITIES 385

11.1 Introduction, 385

11.2 Theory, 389

11.2.1 A Simple Random Sample with Nonresponse, 389

11.2.2 A Self-Selection Sample, 392

11.2.3 The Response Propensity Definition, 393

11.2.4 Models for Response Propensities, 394

11.2.5 Correction Methods Based on Response Propensities, 401

11.3 Application, 406

11.3.1 Generation of the Population, 407

11.3.2 Generation of Response Probabilities, 408

11.3.3 Generation of the Sample, 408

11.3.4 Computation of Response Propensities, 408

11.3.5 Matching Response Propensities, 409

11.3.6 Estimation of Population Characteristics, 411

11.3.7 Evaluating the Results, 412

11.3.8 Model Sensitivity, 412

11.4 Summary, 413

12 WEB PANELS 419

12.1 Introduction, 419

12.2 Theory, 422

12.2.1 Web Panel Definition and Recruitment, 422

12.2.2 Use of Web Panels, 426

12.2.3 Web Panel Management, 427

12.2.4 Response Rates, 432

12.2.5 Representativity, 443

12.3 Application, 449

12.4 Summary, 451

Key Terms, 452

Exercises, 452

References, 454

INDEX 459

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