Applied Statistical Research Methods

When conducting research into frailty, among other things, a lot of data from patients and professionals becomes available with which socially important research questions can be answered.

The Applied Statistical Research Methods research group has many partnerships with research groups within the Centre of Expertise Healthy Aging and researchers from the field. It is daily work to apply new techniques from statistics and artificial intelligence, often with the aid of the statistical programming language R. Techniques such as mixed modeling, statistical learning, and model selection go hand in hand with data visualisations. Much research falls under the research lines Assessment, Outcome Analysis, and Research Design, which address questions such as:

  • How can responses of participants to questionnaire items best be analyzed so that the underlying concept of 'frailty', 'willingness to use information technology' or 'reciprocity in the workplace' is properly measured?
  • Which techniques can best be used to analyze the effect of interventions in health care, in which patients are measured repeatedly?
  • How many patients are needed for a given statistical design?
  • What conclusions can be drawn from several published studies on the same problem and what does this mean for practice?