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.
BlumenthalM., 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.
BrockmanD. and JoshuaK., 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.
DajaniA. and RodrickJ., 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.
FarandaR., 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.
KennickelA., Curbstoning and culture, Statistical Journal of the IAOS31(2) (2015).
9.
KoczelaS., C Furlong, MccarthyJ. and MushtaqA., Curbstoning and beyond: Confronting data fabrication in survey research, Statistical Journal of the IAOS31(3) (2015), 413-422.
10.
CrespiL.P., The cheater problem in polling, Public Opinion Quarterly9(4) (1945), 431-445.
11.
LacourM. and DonaldG., When contact changes minds: An experiment on transmission of support for gay equality, Science346(6215) (12 December 2014), 1366-1369. (Retracted)
12.
LavrakasP., Encyclopedia of Survey Research Methods (2 volumes), SAGE, 2008.
13.
MurphyJ., PaulB., ChrisS., RitaT., OrinD. and PatrickH., Interviewer falsification: Current and best practices for prevention, detection, and mitigation, Statistical Journal of the IAOS, current issue.
14.
MushtaqA., Detection techniques applied, Paper presented at Washington Statistical Society - Curb-stoning, a Too Neglected and Very Embarrassing Survey Problem, December 2014, Washington DC.
15.
ParsonsJ. and IsabelF., Approaches for detecting fabricated survey data. Paper presented at New Approaches to Dealing With Survey Data Fabrication conference, NORC, Bethesda, MD, 2016.
16.
RobbinsM. and NobleK., 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.
SimmonsK., AndrewM., SteveS. and CourtneyK., Evaluating a new proposal for detecting data falsification in surveys, Statistical Journal of the IAOS, current issue.
19.
SpagatM., Suspicious supervisors and suspect surveys, Stats.org, Accessed August 25, 2016 from http://www.stats. org/suspicious-supervisors-suspect-surveys/.
20.
SpagatM., Comment on Don't get duped: Fraud through duplication in public opinion surveys, Statistical Journal of the IAOS, current issue. bibitem21 WinkerP., Assuring the quality of survey data: Incentives, detection and documentation of deviant behavior, Statistical Journal of the IAOS, current issue.
