The present paper contrasts two related criteria for the evaluation of prior-data conflict: the Data Agreement Criterion (DAC; Bousquet, 2008) and the criterion of Nott et al. (2016). One aspect that these criteria have in common is that they depend on a distance measure, of which dozens are available, but so far, only the Kullback-Leibler has been used. We describe and compare both criteria to determine whether a different choice of distance measure might impact the results. By means of a simulation study, we investigate how the choice of a specific distance measure influences the detection of prior-data conflict. The DAC seems more susceptible to the choice of distance measure, while the criterion of Nott et al. seems to lead to reasonably comparable conclusions of prior-data conflict, regardless of the distance measure choice. We conclude with some practical suggestions for the user of the DAC and the criterion of Nott et al.

Lek, K. & Van De Schoot, R. (2019). How the Choice of Distance Measure Influences the Detection of Prior-Data Conflict. Entropy21, 446.



PhD Student

Kimberley works together with Rens on how educational and psychological tests can be improved with new and existing statistical tools. One project focusses, for instance, on how (un)certainty in the test results of individual examinees can be estimated and expressed, to ...