Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference

19 Jul 2017 Tchetgen Eric J. Tchetgen Wang Linbo Sun BaoLuo

Nonmonotone missing data arise routinely in empirical studies of social and health sciences, and when ignored, can induce selection bias and loss of efficiency. In practice, it is common to account for nonresponse under a missing-at-random assumption which although convenient, is rarely appropriate when nonresponse is nonmonotone... (read more)

PDF Abstract
No code implementations yet. Submit your code now