On the testability of the CAR assumption

Journal article (2004)

Authors

Faculty
Electrical Engineering, Mathematics and Computer Science (EEMCS) (TU Delft)
Copyright: © Institute of Mathematical Statistics
DOI: https://doi.org/doi:10.1214/009053604000000418
More Info
expand_more

Published Date

01-03-2004

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Source:

Annals of Statistics. Volume 32, Number 5 (2004), 1957-1980.

Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

In recent years a popular nonparametric model for coarsened data is an assumption on the coarsening mechanism called coarsening at random (CAR). It has been conjectured in several papers that this assumption cannot be tested by the data, that is, the assumption does not restrict the possible distributions of the data. In this paper we will show that this conjecture is not always true; an example will be current status data. We will also give conditions when the conjecture is true, and in doing so, we will introduce a generalized version of the CAR assumption. As an illustration, we retrieve the well-known result that the CAR assumption cannot be tested in the case of right-censored data.

Files

Cator.pdf
(pdf | 0.185 Mb)