Identifikation von Fälschungen in Surveys
Leader: Dr. Natalja Menold
Scientific unit: Survey Design and Methodology
Survey data might be subject to falsifications by interviewers. Based on an analysis of the motivation for such falsifications we develop, test and apply multivariate statistical methods, which can be used to identify falsifications in survey data. The methods build on specific properties of falsified interviews, e.g., with regard to the number of unanswered questions or the distributions of digits, and their interdependence. The grouping of actual interview data is performed using these criteria when applying clustering methods. We also consider heuristic optimisation algorithms for obtaining the best possible clusters for different criteria. Furthermore, if ex ante information on falsifications is available, discriminant analysis is used to identify typical properties of false interviews.
In parallel to the analysis of the statistical methods, we develop design features of questionnaires, which increase the chance of ex post detection of falsifications. Thereby, the quality of survey data is expected to improve both due to the ex post identification of faked interviews and an increased deterrence effect. Questionnaire designs and statistical methodology are tested in an experimental setting.