About the Book
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.
Table of Contents:
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
About the Author :
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.
