Data quality
Data rarely just come about. They are often produced as a by-product of another process (e.g. browsing histories on the web) or have to be actively collected. Data can take many forms: our department focuses on designing and evaluating methodologies for collecting data using questionnaires survey methodology, data donation, developing innovative methodologies for producing official statistics, and dealing with missing data.
The goal of data collection methodologies is that the resulting data are fit for purpose: they have to measure what they are intended to measure, do so consistently over time, and be produced in a timely and efficient manner. In other words, the methodologies have to produce data that are transparent and reproducible. Most of the time, data that are available are incomplete; we study imputation and nonresponse correction models to deal and correct for missing data.
In this research area we collaborate intensively with other researchers, as well as institutes that collect data. In particular, we collaborate with Statistics Netherlands, the National Institute for Public Health and the Environment (RIVM), and several branches of government (local and national).
This theme includes the following topic areas:
