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.
Dokumententyp: | Paper |
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Keywords: | coarse data, missing data, coarsening at random (CAR), likelihood-ratio test, partial identification, sensitivity analysis |
Fakultät: | Mathematik, Informatik und Statistik > Statistik > Technische Reports |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
JEL Classification: | C |
URN: | urn:nbn:de:bvb:19-epub-36407-6 |
Sprache: | Englisch |
Dokumenten ID: | 36407 |
Datum der Veröffentlichung auf Open Access LMU: | 24. Mrz. 2017, 12:46 |
Letzte Änderungen: | 04. Nov. 2020, 13:14 |