Web Survey Bibliography
In the last few years, it has become possible to conduct meaningful behavioral research via the Internet. As of June 17, 1998, there were 35 Internet experiments and surveys in the American Psychological Society list of Psychological Research on the Net, maintained by John Krantz, URL [http://psych.hanover.edu/APS/exponnet.html]. By May 11, 1999, this figure had grown to 65, suggesting a growth rate of about 100% per year. I expect that this book and others like it will accelerate this growth. Of the experiments listed in the APS Web site, there were 24 in social psychology, 13 in cognitive, 8 in sensation/perception, 5 in health psychology, 4 in developmental, 3 in clinical, 3 in personality and industrial-organizational, 2 in biological, 2 in emotions, and one in general psychology. Although this list does not include all experiments, it gives a proportional estimate that indicates the growth of research conducted via the Web. Early "pioneers" of Internet research soon learned that it was not only possible to conduct research this way, but that it was also feasible to collect large samples of high quality data in a short period of time. This book is intended for psychologists who are interested in learning from the experiences of those who have been engaged in this type of research. The book includes a great deal of good advice from those who have learned by experience. In reading the book, you should follow suggested links on your computer, which should be your window to the Web and your study companion. This Web page includes the most important links from the book, which will save you the trouble of typing in the URLs (the addresses of the sites on the Web). One advantage of Web-based research is the ease with which another can see exactly what the participants experienced and also learn how the experimenter carried it out. To save space (and trees), the authors have made a great deal of information available to you electronically via the Internet. Terms used in the book unique to this type of research (e.g., HTTP, HTML, FTP, etc.) are defined in a glossary at the end of the book. The book has three sections. The first deals with general questions such as do the results of Web experiments agree with those of laboratory experiments? Who are the people who volunteer to participate via the Internet? What were the developments that led to the first Web studies and what did the early Web researchers experience? What are the methodological considerations in doing research by "remote control?" The second section considers studies of individual differences and cultural differences. Because the Internet provides a means to reach large and diverse samples, it seems ideally suited for these purposes. The third section covers advanced computer techniques that allow for greater control of Internet experiments. These include the dynamic creation and display of graphics, randomization, and timing in experiments such as those in cognitive experimental psychology. In addition, methods for scoring and feedback on surveys or tests, tracking of participants, security, and saving of data on the server are discussed.
Homepage - book (abstract)
Web survey bibliography (4086)
- The Best of Both Worlds: Utilizing Best Practices From Web and Survey Design ; 2016; Libman Barry, A.; Langer Tesfaye, C.; Levy, J.
- Characterizing Satisficers in Web Surveys Using Paradata to Target Interventions; 2016; Vetting, S. S.; Horwitz, R.; Bray, R.; Hernandez Vivier, A.; Tancreto, J.; Reiser, C.
- A Closer Look at Response Time Outliers in Online S urveys Using Paradata Survey Focus ; 2016; Schlosser, S.; Hoehne, J. K.
- Exploring Mode Effects Between Smartphone and Perso nal Computer Mode of Administration of a National...; 2016; Fahrney Wiant, K.; Richards, A.; Zimmer, S.; Mayclin, D.
- Response Order Effects on a Web Survey of Nurse Pra ctitioners ; 2016; Quintana, G.; Riley, L. E.
- Using Paradata to Identify Questions with High Resp ondent Burden for Improvement in Future Surveys ; 2016; Powell, R.Richards, A.Yu, S.Brackbill, R.
- Investigating Cognitive Effort of Response Formats in Web Surveys using Paradata ; 2016; Hoehne, J. K.; Schlosser, S.; Krebs, D.
- Assessing the Effects and Effectiveness of Attention-check Questions in Web Surveys: Evidence From a...; 2016; Vannette, D.
- Conducting Survey Experiments Using an Online Labor Market ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Ferrer, R.; Berrigan...
- Mode Effect on Racial Sensitive Questions between W eb and Computer-assisted Self-interview ; 2016; Liu, M.; Wang, Y.; Lepkowski, J. M.
- A Test of Web/PAPI Protocols and Incentives for the Residential Energy Consumption Survey ; 2016; Biemer, P. P.; Murphy, J.; Zimmer, S.; Berry, J.; Lewis, K.; Shaofen, D.
- Mode Effects in American Trends Panel: Bayesian Analysis of a Cross-classified Item-person Mixed Model...; 2016; Gill, Je.; Kolenikov, S.; McGeeney, K.
- Mobile Device Use in Web Surveys Among College Students: Predictors and Consequences for Data Quality...; 2016; Beach, S.; Musa, D.; Strotmeyer, S.; Schlarb, J.
- Mode Effects on Subjective Well-being Research: Do they Affect Regression Coefficients? ; 2016; Sanchez Tome, R.; Roberts, C.; Staehli, M. E.; Joye, D.
- Effects of an Initial Offering of Multiple Survey Response Options on Response Rates; 2016; Steele, E. A.; Marlar, J.; Allen, L.; Kanitkar, K. N.
- How to Invite? Methods for Increasing Internet Surv ey Response Rate ; 2016; Huang, A. R.; Noel, H.; Hargraves, L.
- The Mobile Web Only Population: Socio-demographic Characteristics and Potential Bias ; 2016; Fuchs, M.; Metzler, A.
- Unintentional Mobile Respondents in Official Statis tics and Their Effect on Data Quality ; 2016; Bakker, J.
- Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages ; 2016; West, B. T.; Ghimire, D.; Axinn, W.
- Testing Web-Based Survey Measures of Gender Identity and Sexual Orientation Using Mark-All-That-Apply...; 2016; Brenner, P.; Bulgar - Medina, J.
- Mode and Eligibility Rates in a Dual-mode Web and Mail Survey ; 2016; Ventura, I.; Bilgen, I.; Stern, M. J.
- The Impact of Response Scale Direction on Survey Responses in a Mixed-mode Survey ; 2016; Hu, M.; Yan, T.; Keusch, F.
- Examining Trends in the Presence of Survey Mode Effects ; 2016; Hisako Kitada, H.; Lesser, V. M.
- Best Practice Instrument & Communications Evaluation: An Examination of the NSCH Redesign ; 2016; Higgins, W. B.; Welch, R.; Tortora, R. D.; Vladutiu, C. J.
- The Effect of Respondent Commitment and Tailored Fe edback on Response Quality in an Online Survey ; 2016; Cibelli Hibben, K.; Conrad, F. G.
- Effectiveness of Messaging to Encourage Response to the ACS ; 2016; Fulton, J.; Hunter Childs, J. E.; Morales, G.
- Reaching the Mobile Generation: Reducing Web Survey Non-response through SMS Reminders ; 2016; Kanitkar, K. N.; Marlar, J.
- The Effect of Using Text Messages for Survey Invitations and Reminders ; 2016; McGeeney, K.; Yan, H. Y.
- "Don't be Afraid ... We're Researchers!": The Impact of Informal Contact Language...; 2016; Foster, K. N.; Hagemeier, N. E.; Alamain, A. A.; Pack, R.; Sevak, R. J.
- Does Embedding a Survey Question in the Survey Invi tation E-mail Affect Response Rates? Evidence from...; 2016; Vannette, D.
- Mode Effects in Electoral Polls: A Comparative Perspective ; 2016; Durand, C.
- Safety First: Ensuring the Anonymity and Privacy of Iranian Panellists’ While Creating Iran...; 2016; Farmanesh, A.; Mohseni, E.
- Novel Methodology for Reaching a Statewide Represen tative Sample of Youth Ages 12-18 ; 2016; Freedner-Maguire, N.; ZuWallack, R. S.
- Communication Channels that Predict and Mediate Self-response ; 2016; Walejko, G. K.
- Encouraging Online Response among Hard-to-Survey Po pulations: Digital Advertising and Influencer Calls...; 2016; Bates, N.; Virgile, M.
- ...; 2016; Mccaffrey, K. M.; Otmany, J.; Hagedorn, S.
- Simulating a Census Environment to Test Online Self -response ; 2016; Vines, M.
- Using a Response Propensity Model to Allocate Non-c ontingent Incentives in a Web Panel ; 2016; Masterton, M.
- Promoting Participation in Web Surveys; 2016; Hupp, A.; Chan, W.
- Does Asking for Linkage Consent in the Beginning of the Questionnaire Affect Respondents' Answers...; 2016; Haas, G. C.; Eckman, S.
- Implications of Response Device Type for Sensitive Web Surveys: Examining Data Quality and Respondent...; 2016; C.; Richards, A.; C.; Peterson, K.; Smith, A. C.
- Influence of Multiple Factors on Response Rate; 2016; Chaney,B.H.; Chaney, B. H.; Kindlon, A.
- What’s Your Number? Evaluating the Success of Telep hone Number Acquisition Via Record Match,...; 2016; Linville, J. C.; Carley- R.; Carley- R.; Grant, D. B.; Carley- R.; Jans, M.; Carley- R.; Park, R.; Becker...
- Tracking the Representativeness of an Online Panel Over Time ; 2016; Klausch, L. T.; Scherpenzeel, A.
- Can Using a Mixed Mode Approach Improve the Representativeness and Data Quality in Panel Surveys?; 2016; Stern, M. J.
- Surveying American Indian and Alaska Native Parents : Identifying Characteristics of Survey Mode Preference...; 2016; Feeney, K.; Masters, F.
- The Impact of Scale Direction, Alignment and Length on Responses to Rating Scale Questions in a Web...; 2016; Keusch, F.; Liu, M.; Yan, T.
- Pre-election Surveys Using a Multi-modal Interviewing Strategy ; 2016; Redman, J.; Thompson, Sc.; Yost, B.
- Methods for Detecting Telescoping Error in a Cross- sectional Web Design Survey ; 2016; Shook-Sa, B. E.; Berzofsky, M.; Peterson, K.; Lindquist, C.; Krebs, C.
- Introduction Breakoffs, Questionnaire Breakoffs and Web Questionnaire Length: A Metastudy ; 2016; Cehovin, G.; Vehovar, V.