Handbook of web surveys / Silvia Biffignandi, Jelke Bethlehem.

By: Biffignandi, Silvia [author.]
Contributor(s): Bethlehem, Jelke G [author.]
Language: English Publisher: Hoboken, NJ : Wiley, 2021Edition: Second editionDescription: 1 online resource (xv, 607 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119371717Subject(s): Internet surveys | Surveys -- MethodologyGenre/Form: Electronic books.DDC classification: 001.4/33 LOC classification: HM538Online resources: Full text is available at Wiley Online Library Click here to view.
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 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
Summary: "Web surveys have become a popular means of data collection. It is a cheap and fast way to collect data potentially large group of people. Carrying out a web survey, however, also involves a number of methodological issues. Researchers conducting web-based survey research must understand (1) major sources of survey error associated with this kind of data collection and current approaches to addressing these problems; (2) current best practices for the conducting this kind of research, such as the basic principles of web survey questionnaire design; and (3) the advantages and disadvantages of web surveys, relative to other survey data collection modes"-- Provided by publisher.
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001.433 B479 2021 (Browse shelf) Available
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Includes bibliographical references and index.

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

Available to OhioLINK libraries.

"Web surveys have become a popular means of data collection. It is a cheap and fast way to collect data potentially large group of people. Carrying out a web survey, however, also involves a number of methodological issues. Researchers conducting web-based survey research must understand (1) major sources of survey error associated with this kind of data collection and current approaches to addressing these problems; (2) current best practices for the conducting this kind of research, such as the basic principles of web survey questionnaire design; and (3) the advantages and disadvantages of web surveys, relative to other survey data collection modes"-- Provided by publisher.

Jelke Bethlehem, PhD, is Professor by special appointment in survey methodology at Leiden University, Netherlands. He is also senior methodological advisor at Statistics Netherlands in The Hague. He is coauthor of Handbook of Nonresponse in Household Surveys, Handbook of Web Surveys (First Edition), and Applied Survey Methods: A Statistical Perspective, published by Wiley. Dr. Bethlehem is also coeditor of Online Panel Research: A Data Quality Perspective and Computer Assisted Survey Information Collection, also published by Wiley.

Silvia Biffignandi is Professor of Economic and Business Statistics at the University of Bergamo in Italy, where she is also Director of the Centre for Statistical Analyses and Survey Interviewing (CASI). Dr. Biffignandi is coauthor of Handbook of Web Surveys (First Edition), published by Wiley.

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