Modular Questionnair Designs for Social Surveys: Statistical Modelling of Missingness in Real Social Survey Data 2 (ModuQuD 2)

This project investigates how imputation procedures can be applied in social surveys collected by using so-called modular questionnaire designs. Imputing these data can be challenging due to the typical features of social survey data, such as predominantly low correlations between variables, a possible large number of variables combined with relatively small samples, and often a large number of categorical variables in the dataset. In the first phase of the project, we have identified promising strategies to deal with these challenges. However, to meet the requirements for the applications of modular questionnaire designs in social surveys, the imputation procedures need to be further developed. For example, this is related to the application of imputation methods for multinominal data, to the application of the methods with several hundred variables and the application of complex multivariate models, which are often used in the social sciences. The examination of these applications is the research aim of the second project phase.