Abstract: In this paper, the mean-value estimation problem with surrogate data and validation sampling is considered. A regression calibration kernel function is defined to incorporate the information contained in both surrogate variates and validation sampling. The proposed estimators are proved to be asymptotically normal and convergent rate.