You are viewing a javascript disabled version of the site. Please enable Javascript for this site to function properly.
Go to headerGo to navigationGo to searchGo to contentsGo to footer
In content section. Select this link to jump to navigation

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.