Department of Statistics
Boise State University
Institutional Affiliation: Boise State University
NBER Working Papers and Publications
|August 2010||A Semiparametric Approach for Analyzing Nonignorable Missing Data|
with , : w16270
In missing data analysis, there is often a need to assess the sensitivity of key inferences to departures from untestable assumptions regarding the missing data process. Such sensitivity analysis often requires specifying a missing data model which commonly assumes parametric functional forms for the predictors of missingness. In this paper, we relax the parametric assumption and investigate the use of a generalized additive missing data model. We also consider the possibility of a non-linear relationship between missingness and the potentially missing outcome, whereas the existing literature commonly assumes a more restricted linear relationship. To avoid the computational complexity, we adopt an index approach for local sensitivity. We derive explicit formulas for the resulting semiparam...
Published: Xie, Hui, Yi Qian and Leming Qu. 2011. A Semiparametric Approach for Analyzing Nonignorable Missing Data. Statistica Sinica. 21: 1881-1899.