Interviewer effects in real and falsified interviews: Results from a large scale experiment

Winker, Peter; Kruse, Karl-Wilhelm; Menold, Natalja; Landrock, Uta

doi:10.3233/sji-150908

Cited by 11 publications

(12 citation statements)

References 13 publications

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“…Kreuter et al (2011) report that payment per hour did not alter interviewer effects associated with responses to filter questions, compared to payment per completed interview. By contrast, Winker et al (2015) found that experimentally and randomly varied payment schemes (payment per hour vs. per completed interviews) had an effect on the interview data (e.g., interview durations).…”

Section: Introductionmentioning

confidence: 79%

The Impact of Payment and Respondents’ Participation on Interviewers’ Accuracy in Face-to-face Surveys

et al. 2018

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In face-to-face interviews, accurate work by interviewers is crucial for ensuring high-quality survey data. In a field experiment, payment of interviewers, legitimation of falsification behavior, and respondents' willingness to participate were experimentally varied. The impact of these factors on interviewers' accuracy during fieldwork was investigated. Low accuracy was operationalized, for instance, as noncompliance with the instructions concerning contacting and recruitment. In addition, falsifications by

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Section: Introductionmentioning

confidence: 79%

The Impact of Payment and Respondents’ Participation on Interviewers’ Accuracy in Face-to-face Surveys

et al. 2018

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“…[18]). The database in this paper consists of three datasets, obtained in the summer of 2011, and is described in detail by Kemper and Menold [19] as well as by Menold and Kemper [7]:…”

Section: Database and Methodsmentioning

confidence: 99%

“…As a result, some of the sociodemographic variables, like age or education, show only small variances (cp. [18]). …”

Section: Database and Methodsmentioning

confidence: 99%

Explaining political participation: A comparison of real and falsified survey data

Landrock¹

2017

SJI

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Abstract. This paper examines differences between real survey data and data falsified by interviewers. Previous studies show that there are only small differences between real and falsified data which implies that falsifying interviewers are able to (re-)produce realistic frequency distributions. The question this paper aims to answer is whether they are also able to produce multivariate results in accordance with the assumptions of established social science approaches. As an example for a realistic theory-driven data analysis, real and falsified data are compared in terms of the identified determinants of political participation. I use an experimental data set with data partly collected in real interviews and partly by interviewers being instructed to falsify; that is, to fill in the questionnaire based on little information about the respondent. The questionnaire measures twelve political activities, based on which I calculate an index for political participation. There are differences in the models between the real and the falsified data: The explained variances are higher in the regression models of the falsified data. There are some variables significant in both data sets and some that are significant only in the real or in the falsified data. These differences can be explained by our theoretical assumptions.

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“…As long as data quality issues do not become public, it appears rational for the field agency not to discuss them with the researcher nor to invest effort on repeating (parts) of the survey at its own cost. It is also rational to pay interviewers per completed interview although it is known that payment per hour reduces the risk of deviant behavior and improves the quality of collected data as does a careful training and supervision of interviewers [16,25,33].…”

Section: Incentivesmentioning

confidence: 99%

“…Thus, for a full picture of deviant behavior, which might be used to improve and evaluate detection methods, access to many more real datasets with identified deviant behavior is required. When it comes to evaluate the performance of specific detection methods for specific types of deviant behavior, experimental and simulated data sets might be used to complement the findings from real data [3,31,33].…”

Section: Documentation and Reputationmentioning

confidence: 99%

Assuring the quality of survey data: Incentives, detection and documentation of deviant behavior

Winker

2016

SJI

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Abstract. Research data are fragile and subject to classical measurement error as well as to the risk of manipulation. This also applies to survey data which might be affected by deviant behavior at different stages of the data collection process. Assuring data quality requires focusing on the incentives to which all actors in the process are exposed. Relevant actors and some specific incentives are presented. The role of data based methods for detection of deviant behavior is highlighted as well as limitations when actors are aware of them. Conclusions are drawn on how settings can be improved to provide positive incentives. Furthermore, it is stressed that a proper documentation of data quality issues in survey data is required both in order to increase trust in the data eventually used for analysis and to provide input for the development of new methods for detection of deviant behavior.

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Interviewer effects in real and falsified interviews: Results from a large scale experiment

Cited by 11 publications

References 13 publications

The Impact of Payment and Respondents’ Participation on Interviewers’ Accuracy in Face-to-face Surveys

The Impact of Payment and Respondents’ Participation on Interviewers’ Accuracy in Face-to-face Surveys

Explaining political participation: A comparison of real and falsified survey data

Assuring the quality of survey data: Incentives, detection and documentation of deviant behavior

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