An Extended Single-index Model with Missing Response at Random

摘要

An extended single-index model is considered when responses are missing at random. A three-step estimation procedure is developed to define an estimator for the single-index parameter vector by a joint estimating equation. The proposed estimator is shown to be asymptotically normal. An algorithm for computing this estimator is proposed. This algorithm only involves one-dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Some simulation studies are conducted to investigate the finite sample performances of the proposed estimators.