  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.

Methodology