SSOAR Logo
    • Deutsch
    • English
  • English 
    • Deutsch
    • English
  • Login
SSOAR ▼
  • Home
  • About SSOAR
  • Guidelines
  • Publishing in SSOAR
  • Cooperating with SSOAR
    • Cooperation models
    • Delivery routes and formats
    • Projects
  • Cooperation partners
    • Information about cooperation partners
  • Information
    • Possibilities of taking the Green Road
    • Grant of Licences
    • Download additional information
  • Operational concept
Browse and search Add new document OAI-PMH interface
JavaScript is disabled for your browser. Some features of this site may not work without it.

Download PDF
Download full text

(external source)

Citation Suggestion

Please use the following Persistent Identifier (PID) to cite this document:
https://doi.org/10.12758/mda.2021.02

Exports for your reference manager

Bibtex export
Endnote export

Display Statistics
Share
  • Share via E-Mail E-Mail
  • Share via Facebook Facebook
  • Share via Bluesky Bluesky
  • Share via Reddit reddit
  • Share via Linkedin LinkedIn
  • Share via XING XING

Do Falsifiers Leave Traces? Finding Recognizable Response Patterns in Interviewer Falsifications

[journal article]

Walzenbach, Sandra

Abstract

Fraud by interviewers is a ubiquitous threat to data quality in survey practice, whenever face-to-face surveys are conducted. Particularly if interviewers use stereotypes about respondents to fill in questionnaires, falsifications can limit the variety of possible answers, lead erroneously to signif... view more

Fraud by interviewers is a ubiquitous threat to data quality in survey practice, whenever face-to-face surveys are conducted. Particularly if interviewers use stereotypes about respondents to fill in questionnaires, falsifications can limit the variety of possible answers, lead erroneously to significant correlations and distort survey results. In addition to external control mechanisms to detect fraud (such as postcards or time stamps) more recent research has started to also consider internal indicators (such as the number of missing values or open answers) as a monitoring strategy. This latter approach relies on ex-post statistical analyses and implicitly assumes that falsifiers apply rational behavioral strategies which result in detectable response patterns. This study examines to what extent fieldwork monitoring can benefit from such approaches, by empirically assessing how effective different indicators are at detecting known cases of fabrication. In contrast to most previous research, which often relies on laboratory fabrications, this study uses authentic cases of detected interviewer fraud from a survey on the fairness of earnings conducted in Germany. The main goal of this study is to examine to what extent the falsifiers’ attempts to produce unsuspicious data led to recognizable response patterns. For this purpose, we test a wide range of indicators that could potentially identify falsifications: avoidance of extreme categories and open text-based answers, low rates of item-nonresponse, strategic use of filter questions to shorten the questionnaire and non-compliance of responses to numeric questions with Benford‘s Law. Furthermore, we compare authentic and fabricated interviews according to their values on a social desirability scale and report results from an innovative trick question that was especially designed to detect falsifiers.... view less

Keywords
survey research; data quality; interview; reactivity effect

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
interviewer falsification; interviewer fraud; interviewer effects; response patterns; statistical methods

Document language
English

Publication Year
2021

Page/Pages
p. 125-160

Journal
Methods, data, analyses : a journal for quantitative methods and survey methodology (mda), 15 (2021) 2

ISSN
2190-4936

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution 4.0


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.
 

 


GESIS LogoDFG LogoOpen Access Logo
Home  |  Legal notices  |  Operational concept  |  Privacy policy
© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.