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Activity Number: 6 - Recent Advance of Nonparametric and Semiparametric Techniques with Complex Data Structure
Type: Invited
Date/Time: Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #326676 Presentation
Title: A Profile Likelihood Approach to Semiparametric Estimation with Nonignorable Nonresponse
Author(s): Jae-kwang Kim* and Kosuke Morikawa and Hejian Sang
Companies: Iowa State University and Osaka University and Iowa State University
Keywords: Estimating functions; Identification ; Incomplete data ; Not missing at random

Statistical inference with nonresponse is quite challenging, especially when the response mechanism is not missing at random. The existing methods often require correct model specification for both the outcome regression model and the response model. However, due to nonresponse, both model assumptions cannot be verified from the data and model mis-specification can lead to biased inference seriously. To overcome this limitation, we develop a robust semiparametric method based on the profile likelihood obtained from semiparametric response model. The proposed method uses the observed regression model and the semiparametric response model to achieve robustness. A computational algorithm using fractional imputation is developed. The bootstrap testing procedure is also proposed to test ignorability assumption. The consistency and asymptotic normality of the proposed method are established. The finite-sample performance is examined in the limited simulation studies and an application to the Korean Labor and Income Panel Study dataset is also presented.

Authors who are presenting talks have a * after their name.

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