Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

10-31-2018

Journal or Book Title

arxiv

Abstract

How to deal with nonignorable response is often a challenging problem encountered in statistical analysis with missing data. Parametric model assumption for the response mechanism is often made and there is no way to validate the model assumption with missing data. We consider a semiparametric response model that relaxes the parametric model assumption in the response mechanism. Two types of efficient estimators, profile maximum likelihood estimator and profile calibration estimator, are proposed and their asymptotic properties are investigated. Two extensive simulation studies are used to compare with some existing methods. We present an application of our method using Korean Labor and Income Panel Survey data.

Comments

This pre-print is made available through arxiv: https://arxiv.org/abs/1810.12519.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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