Outlook and Discussion
Statistical identification methods have been demonstrated to be effective and are becoming increasingly popular tools for identifying falsified interviews in surveys. Through the combined use of different analysis tools, it is possible to create comprehensive measures that can identify various types of falsification and can be particularly useful for improving and supporting traditional quality control procedures. They can be automated to flag suspicious interviewers early in the field period for more extensive quality control procedures. However, so far no empirical threshold is defined on how early results become reliable, which should be addressed in future research. Although various statistical methods for detecting falsification exist, research into new and improved methods is still ongoing. Unfortunately, appropriate data for investigating falsification and testing and evaluating new and existing detection methods are often not made available to researchers. This is due to the small number of falsified interviews, but also because falsified data are usually removed from the published data upon detection. Due to the cooperativeness of our survey institute, we were able to demonstrate the usefulness of the different statistical tools for a high-profile case of interviewer falsification. By routinely making such data available to the research community, survey institutes would make a great contribution to the discussion about interviewer falsification and facilitate the development and improvement of quality control methods.
Financial support from the Charles Cannell Fund in Survey Methodology is gratefully acknowledged.
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