Handbook of Web Surveys

Handbook of Web Surveys presents a self-contained guide to methodological issues related to web surveys, covering both theoretical and practical aspects of the topic. The book first approaches the subject of web survey design, addressing the main question: How can an electronic questionnaire be designed such that respondents can complete it on the Internet without introducing (too many) errors? The second portion of the book is devoted to sampling issues and helping readers understanding how proper samples for web surveys can be selected to allow for unbiased estimation of population characteristics. The authors also explore the topics of under-coverage, self-selection, adjustment weighting, and propensity scores as they pertain to effective web survey development. Each chapter follows the same easy-to-follow format. Following an introduction, a description of theory is presented along with key formulae. Next, the discussed theory is applied to a real data set and accompanied with illustrative descriptions. Example sets and exercises are spread throughout each chapter, and a summary provides a brief overview of main points and concepts. Real data is used throughout the book, and a related Web site features additional data sets, interactive simulations, and solutions to exercises.

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.

Preface	p. xi
The Road to web surveys	p. 1
Introduction	p. 1
Theory	p. 2
The Everlasting Demand for Statistical Information	p. 2
The Dawn of Sampling Theory	p. 4
Traditional Data Collection	p. 8
The Era of Computer-Assisted Interviewing	p. 10
The Conquest of the Web	p. 12
Application	p. 21
Summary	p. 31
Key Terms	p. 31
Exercises	p. 33
References	p. 34
About web surveys	p. 37
Introduction	p. 37
Theory	p. 40
Typical Survey Situations	p. 40
Why On-Line Data Collection?	p. 45
Areas of Application	p. 48
Trends in Web Surveys	p. 50
Application	p. 52
Summary	p. 55
Key Terms	p. 56
Exercises	p. 56
References	p. 58
Sampling for web surveys	p. 59
Introduction	p. 59
Theory	p. 60
Target Population	p. 60
Sampling Frames	p. 63
Basic Concepts of Sampling	p. 68
Simple Random Sampling	p. 71
Determining the Sample Size	p. 74
Some Other Sampling Designs	p. 76
Estimation Procedures	p. 82
Application	p. 87
Summary	p. 92
Key Terms	p. 92
Exercises	p. 93
References	p. 94
Errors in Web surveys	p. 97
Introduction	p. 97
Theory	p. 103
Measurement Errors	p. 103
Nonresponse	p. 124
Application	p. 133
The Safety Monitor	p. 133
Measurement Errors	p. 134
Nonresponse	p. 136
Summary	p. 138
Key Terms	p. 138
Exercises	p. 140
References	p. 143
Web surveys and other modes of data collection	p. 147
Introduction	p. 147
Modes of Data Collection	p. 147
The Choice of the Modes of Data Collection	p. 149
Theory	p. 152
Face-To-Face Surveys	p. 152
Telephone surveys	p. 158
Mail Surveys	p. 164
Web surveys	p. 169
Application	p. 174
Summary	p. 182
Key Terms	p. 183
Exercises	p. 185
References	p. 187
Designing a web survey questionnaire	p. 189
Introduction	p. 189
Theory	p. 191
The Road Map Toward a Web Questionnaire	p. 191
The Language of Questions	p. 197
Answers Types (Response Format)	p. 200
Basic Concepts of Visualization	p. 211
Web Questionnaires and Paradata	p. 217
Trends in Web Questionnaire Design and Visualization	p. 223
Application	p. 226
Summary	p. 228
Key Terms	p. 228
Exercises	p. 229
References	p. 231
Mixed-Mode surveys	p. 235
Introduction	p. 235
Theory	p. 238
WhatÆs Mixed Mode?	p. 238
Why Mixed Mode?	p. 243
Methodological Issues	p. 248
Mixed Mode for Business Surveys	p. 262
Mixed Mode for Surveys Among Households and Individuals	p. 267
Application	p. 272
Summary	p. 274
Key Terms	p. 274
Exercises	p. 275
References	p. 277
The problem of undercoverage	p. 281
Introduction	p. 281
Theory	p. 287
The Internet Population	p. 287
A Random Sample From the Internet Population	p. 288
Reducing the Noncoverage Bias	p. 290
Mixed-Mode Data Collection	p. 294
Application	p. 295
Summary	p. 299
Key Terms	p. 299
Exercises	p. 300
References	p. 302
The problem of self-selection	p. 303
Introduction	p. 303
Theory	p. 306
Basic Sampling Theory	p. 306
A Self-Selection Sample from the Internet Population	p. 309
Reducing the Self-Selection Bias	p. 314
Application	p. 319
Summary	p. 323
Key Terms	p. 323
Exercises	p. 324
References	p. 326
Weighting adjustment techniques	p. 329
Introduction	p. 329
Theory	p. 334
The Concept of Representativity	p. 334
Poststratification	p. 336
Generalized Regression Estimation	p. 349
Raking Ratio Estimation	p. 358
Calibration Estimation	p. 361
Constraining the Values of Weights	p. 362
Correction Using a Reference Survey	p. 363
Application	p. 372
Summary	p. 378
Key Terms	p. 379
Exercises	p. 380
References	p. 383
Use of response propensities	p. 385
Introduction	p. 385
Theory	p. 389
A Simple Random Sample with Nonresponse	p. 389
A Self-Selection Sample	p. 392
The Response Propensity Definition	p. 393
Models for Response Propensities	p. 394
Correction Methods Based on Response Propensities	p. 401
Application	p. 406
Generation of the Population	p. 407
Generation of Response Probabilities	p. 408
Generation of the Sample	p. 408
Computation of Response Propensities	p. 408
Matching Response Propensities	p. 409
Estimation of Population Characteristics	p. 411
Evaluating the Results	p. 412
Model Sensitivity	p. 412
Summary	p. 413
Key Terms	p. 414
Exercises	p. 414
References	p. 416
Web Panels	p. 419
Introduction	p. 419
Theory	p. 422
Web Panel Definition and Recruitment	p. 422
Use of Web Panels	p. 426
Web Panel Management	p. 427
Response Rates	p. 432
Representativity	p. 443
Application	p. 449
Summary	p. 451
Key Terms	p. 452
Exercises	p. 452
References	p. 454
Index	p. 459
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Handbook of Web Surveys

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