@article { , title = {On the testability of coarsening assumptions: a hypothesis test for subgroup independence}, abstract = {Since coarse(ned) data naturally induce set-valued estimators, analysts often assume coarsening at random (CAR) to force them to be single-valued. Focusing on a coarse categorical response variable and a precisely observed categorical covariate, we re-illustrate the impossibility to test CAR and contrast it to another type of coarsening called subgroup independence (SI), using the data of the German Panel Study ``Labour Market and Social Security'' as an example. It turns out that -- depending on the number of subgroups and categories of the response variable -- SI can be point-identifying as CAR, but testable unlike CAR. A main goal of this paper is the construction of the likelihood-ratio test for SI. All issues are similarly investigated for the here proposed generalized versions, gCAR and gSI, thus allowing a more flexible application of this hypothesis test.}, doi = {10.1016/j.ijar.2017.07.014}, eissn = {0888-613X}, issn = {0888-613X}, journal = {International journal of approximate reasoning}, pages = {292-306}, publicationstatus = {Published}, publisher = {Elsevier}, url = {https://hull-repository.worktribe.com/output/453792}, volume = {90}, keyword = {Specialist Research - Other, Coarse data, Missing data, Coarsening at random (CAR), Likelihood-ratio test, Partial identification, Sensitivity analysis}, year = {2017}, author = {Plass, J. and Cattaneo, M. and Schollmeyer, G. and Augustin, T.} }