Progress in understanding survey data fabrication
References
[1] | AAPOR, Interviewer Falsification in Survey Research: Current Best Methods for Prevention, Detection and Repair of Its Effects, (2003) , Accessed August 26, 2016 from https://www.aapor.org/AAPORKentico/AAPOR_Main/media/MainSite Files/falsification.pdf. |
[2] | AAPOR, Report on Interviewer Falsification, (2005) , Accessed August 26, 2016 from http://www.aapor.org/Education\\-Resources/Reports/Report-to-AAPOR-Standards-Comm-on-Interviewer-Fals.aspx. |
[3] | Blumenthal M., Daily Kos vs. Research 2000 Lawsuit Settled. May 27, 2011, Huffington Post. Accessed August 25, 2011 from http://www.huffingtonpost.com/2011/05/27/daily-kos-research-2000-lawsuit_n_867775.html. |
[4] | Brockman D., and Joshua K., Irregularities in LaCour. Accessed August 26, 2016 from http://stanford.edu/∼ dbroock/ broockman_kalla_aronow_lg_irregularities.pdf. |
[5] | Daily Research News Online. JIR Group Wins Respondent Data Falsification Case. Accessed August 26, 2016 from http: //www.mrweb.com/drno/news22890.htm. |
[6] | Dajani A., and Rodrick J., Marquette, U.S. Census Falsification Detection and Prevention at Census: New Initiatives. Paper presented at Washington Statistical Society - Curb-stoning Part III. June (2015) , Washington DC. |
[7] | Faranda R., The Cheater Problem Revisited: Lessons from Six Decades of State Department Polling. Paper presented at New Frontiers in Preventing, Detecting, and Remediating Fabrication in Survey Research conference, NEAAPOR, Cambridge, MA, (2015) . |
[8] | Kennickel A., Curbstoning and culture, Statistical Journal of the IAOS 31: (2) ((2015) ). |
[9] | Koczela S., , C Furlong, Mccarthy J., and Mushtaq A., Curbstoning and beyond: Confronting data fabrication in survey research, Statistical Journal of the IAOS 31: (3) ((2015) ), 413-422. |
[10] | Crespi L.P., The cheater problem in polling, Public Opinion Quarterly 9: (4) ((1945) ), 431-445. |
[11] | Lacour M., and Donald G., When contact changes minds: An experiment on transmission of support for gay equality, Science 346: (6215) (12 December (2014) ), 1366-1369. (Retracted) |
[12] | Lavrakas P., Encyclopedia of Survey Research Methods (2 volumes), SAGE, (2008) . |
[13] | Murphy J., , Paul B., , Chris S., , Rita T., , Orin D., and Patrick H., Interviewer falsification: Current and best practices for prevention, detection, and mitigation, Statistical Journal of the IAOS, current issue. |
[14] | Mushtaq A., Detection techniques applied, Paper presented at Washington Statistical Society - Curb-stoning, a Too Neglected and Very Embarrassing Survey Problem, December (2014) , Washington DC. |
[15] | Parsons J., and Isabel F., Approaches for detecting fabricated survey data. Paper presented at New Approaches to Dealing With Survey Data Fabrication conference, NORC, Bethesda, MD, (2016) . |
[16] | Robbins M., and Noble K., Don't get duped: Fraud through duplication in public opinion surveys, Statistical Journal of the IAOS, \it Statistical Journal of the IAOS, current issue. |
[17] | Silver, Nate Comparison Study: Unusual Patterns in Strategic Vision Polling Data Remain Unexplained, September 26, 2009, FiveThirtyEight. Accessed August 25, 2016 from http:\\ //fivethirtyeight.com/features/comparison-study-unusual-patterns-in/. |
[18] | Simmons K., , Andrew M., , Steve S., and Courtney K., Evaluating a new proposal for detecting data falsification in surveys, Statistical Journal of the IAOS, current issue. |
[19] | Spagat M., Suspicious supervisors and suspect surveys, Stats.org, Accessed August 25, 2016 from http://www.stats. org/suspicious-supervisors-suspect-surveys/. |
[20] | Spagat M., , Comment on Don't get duped: Fraud through duplication in public opinion surveys, Statistical Journal of the IAOS, current issue. bibitem21 Winker P., Assuring the quality of survey data: Incentives, detection and documentation of deviant behavior, Statistical Journal of the IAOS, current issue. |
