Handbook of Web Surveys
Description
The updated, must-have guide for creating and implementing web surveys
Revised and thoroughly updated, the second edition of Handbook of Web Surveys offers a practical and comprehensive guide for creating and conducting effective web surveys. The authors noted experts on the topic, include a review the Blaise system (which has been around for 30 years) and provide information on the most recent developments and techniques in the field. The book illustrates the steps needed to develop effective web surveys and explains how the survey process should be carried out. It also examines the aspects of sampling and presents a number of sampling designs.
The book includes ideas for overcoming possible errors in measurement and nonresponse. The authors also compare the various methods of data collection (face-to-face, telephone, mail, and mobile surveys) and discuss their advantages and disadvantages. Critical information for designing questionnaires for mobile devices is also provided. Filled with real-world examples, Handbook of Web Surveys discuss the key concepts, methods, and techniques of effective web surveys. This important book:
* Contains the most recent sampling designs and estimation procedures
* Offers ideas for overcoming errors in web surveys
* Includes information on mixed mode surveys
* Explores the concept of response probabilities
* Reviews all aspects of web panels
Written for researchers in government, business, economics, and social scientists, the second edition of Handbook of Web Surveys provides an introduction to web surveys and the various methods and techniques.
More details
Other editions
Additional editions
Previous edition
Persons
SILVIA BIFFIGNANDI is a professor at the Center for Statistics and Analysis of Sample Surveys, University of Bergamo, Bergamo, Italy.
JELKE BETHLEHEM is affiliated with Statistics Netherlands, a Division of Methodology and Quality, The Netherlands.
Content
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 Traditional Data Collection 8
1.2.3 The Era of Computer-Assisted Interviewing 11
1.2.4 The Conquest of the Web 13
1.2.5 Web Surveys and Other Sources 23
1.2.6 Historic Summary 28
1.2.7 Present-Day Challenges and Opportunities 28
1.2.8 Conclusions from Modern-Day Challenges 30
1.2.9 Thriving in the Modern-Day Survey World 30
1.3 Application 31
1.3.1 Blaise 31
1.4 Summary 39
Key Terms 41
Exercises 42
References 44
2 About Web Surveys 47
2.1 Introduction 47
2.2 Theory 50
2.2.1 Typical Survey Situations 51
2.2.2 Why Online Data Collection? 56
2.2.3 Areas of Application 60
2.2.4 Trends in Web Surveys 62
2.3 Application 64
2.4 Summary 68
Key Terms 68
Exercises 69
References 71
3 A Framework For Steps and Errors In Web Surveys 73
3.1 Introduction 73
3.2 Theory 75
3.3 Application 88
3.4 Summary 89
Key Terms 90
Exercises 90
References 91
4 Sampling For Web Surveys 93
4.1 Introduction 93
4.2 Theory 95
4.2.1 Target Population 95
4.2.2 Sampling Frames 98
4.2.3 Basic Concepts of Sampling 103
4.2.4 Simple Random Sampling 106
4.2.5 Determining the Sample Size 109
4.2.6 Some Other Sampling Designs 112
4.2.7 Estimation Procedures 118
4.3 Application 123
4.4 Summary 128
Key Terms 129
Exercises 130
References 131
5 Errors In Web Surveys 133
5.1 Introduction 133
5.2 Theory 142
5.2.1 Measurement Errors 142
5.2.2 Nonresponse 164
5.3 Application 174
5.3.1 The Safety Monitor 174
5.3.2 Measurement Errors 175
5.3.3 Nonresponse 177
5.4 Summary 179
Key Terms 180
Exercises 182
References 185
6 Web Surveys and Other Modes of Data Collection 189
6.1 Introduction 189
6.1.1 Modes of Data Collection 189
6.1.2 The Choice of the Modes of Data Collection 190
6.2 Theory 194
6.2.1 Face-to-Face Surveys 194
6.2.2 Telephone Surveys 200
6.2.3 Mail Surveys 206
6.2.4 Web Surveys 211
6.2.5 Mobile Web Surveys 215
6.3 Application 222
6.4 Summary 230
Key Terms 231
Exercises 233
References 235
7 Designing A Web Survey Questionnaire 237
7.1 Introduction 237
7.2 Theory 240
7.2.1 The Road Map Toward a Web Questionnaire 240
7.2.2 The Language of Questions 249
7.2.3 Basic Concepts of Visualization 252
7.2.4 Answers Types (Response Format) 258
7.2.5 Web Questionnaires and Paradata 271
7.2.6 Trends in Web Questionnaire Design and Visualization 278
7.3 Application 281
7.4 Summary 282
Key Terms 283
Exercises 284
References 286
8 Adaptive and Responsive Design 291
8.1 Introduction 291
8.2 Theory 294
8.2.1 Terminology 294
8.2.2 Quality and Cost Functions 298
8.2.3 Strategy Allocation and Optimization 301
8.3 Application 309
8.4 Summary 316
Key Terms 316
Exercises 317
References 318
9 Mixed-Mode Surveys 321
9.1 Introduction 321
9.2 The Theory 326
9.2.1 What is Mixed-Mode? 326
9.2.2 Why Mixed-Mode? 334
9.3 Methodological Issues 343
9.3.1 Preventing Mode Effects Through Questionnaire Design 346
9.3.2 How to Mix Modes? 350
9.3.3 How to Compute Response Rates? 354
9.3.4 Avoiding and Adjusting Mode Effects for Inference 359
9.3.5 Mixed-Mode by Businesses and Households 370
9.4 Application 384
9.5 Summary 386
Key Terms 388
Exercises 388
References 390
10 The Problem of Under-Coverage 399
10.1 Introduction 399
10.2 Theory 405
10.2.1 The Internet Population 405
10.2.2 A Random Sample from the Internet Population 406
10.2.3 Reducing the Non-Coverage Bias 410
10.2.4 Mixed-Mode Data Collection 413
10.3 Application 414
10.4 Summary 417
Key Terms 418
Exercises 419
References 421
11 The Problem of Self-Selection 423
11.1 Introduction 423
11.2 Theory 431
11.2.1 Basic Sampling Theory 431
11.2.2 A Self-Selection Sample from the Internet Population 434
11.2.3 Reducing the Self-Selection Bias 439
11.3 Applications 444
11.3.1 Application 1: Simulating Self-Selection Polls 444
11.3.2 Application 2: Sunday Shopping in Alphen a/d Rijn 448
11.4 Summary 451
Key Terms 452
Exercises 453
References 455
12 Weighting Adjustment Techniques 457
12.1 Introduction 457
12.2 Theory 463
12.2.1 The Concept of Representativity 463
12.2.2 Post-Stratification 465
12.2.3 Generalized Regression Estimation 477
12.2.4 Raking Ratio Estimation 486
12.2.5 Calibration Estimation 490
12.2.6 Constraining the Values of Weights 491
12.2.7 Correction Using a Reference Survey 492
12.3 Application 500
12.4 Summary 506
Key Terms 508
Exercises 509
References 512
13 Use of Response Propensities 513
13.1 Introduction 513
13.2 Theory 517
13.2.1 A Simple Random Sample With Nonresponse 517
13.2.2 A Self-Selection Sample 520
13.2.3 The Response Propensity Definition 521
13.2.4 Models for Response Propensities 522
13.2.5 Correction Methods Based on Response Propensities 529
13.3 Application 535
13.3.1 Generation of the Population 536
13.3.2 Generation of Response Probabilities 537
13.3.3 Generation of the Sample 537
13.3.4 Computation of Response Propensities 537
13.3.5 Matching Response Propensities 537
13.3.6 Estimation of Population Characteristics 540
13.3.7 Evaluating the Results 541
13.3.8 Model Sensitivity 542
13.4 Summary 542
Key Terms 543
Exercises 544
References 546
14 Web Panels 549
14.1 Introduction 549
14.2 Theory 555
14.2.1 Under-Coverage 555
14.2.2 Recruitment 557
14.2.3 Nonresponse 563
14.2.4 Representativity 577
14.2.5 Weighting Adjustment for Panels 580
14.2.6 Panel Maintenance 582
14.3 Applications 585
14.3.1 Application 1: The Web Panel Pilot of Statistics Netherlands 585
14.3.2 Application 2: The U.K. Polling Disaster 589
14.4 Summary 592
Key Terms 593
Exercises 593
References 595
Index 599
