  We address the weighting problem in voluntary samples under a nonignorable
sample selection model. Under the assumption that the sample selection model is
correctly specified, we can compute a consistent estimator of the model
parameter and construct the propensity score estimator of the population mean.
We use the empirical likelihood method to construct the final weights for
voluntary samples by incorporating the bias calibration constraints and the
benchmarking constraints. Linearization variance estimation of the proposed
method is developed. A limited simulation study is also performed to check the
performance of the proposed methods.
