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Plass, Julia; Cattaneo, Marco E. G. V.; Schollmeyer, Georg; Augustin, Thomas (2017): Testing of Coarsening Mechanisms: Coarsening at Random Versus Subgroup Independence. In: Soft Methods for Data Science, Vol. 456: pp. 415-422
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Since coarse(ned) data naturally induce set-valued estimators, analysts often assume coarsening at random (CAR) to force them to be single-valued. Using the PASS data as an example, we re-illustrate the impossibility to test CAR and contrast it to another type of uninformative coarsening called subgroup independence (SI). It turns out that SI is testable here.