This study investigated the effectiveness of statistical adjustments applied to rater bias in many-facet Rasch analysis. Some changes were first made in the dataset that did not include "rater × examinee" bias to cause to have "rater × examinee" bias. Later, bias adjustment was applied to rater bias included in the data file, and the effectiveness of the statistical adjustment was further examined. The outcomes pertaining to the datasets with and without bias, and to which the bias adjustment was applied, were compared. It was concluded that diversities created by "rater × examinee" bias in examinees' ability estimation, item difficulty indices and measures of rater severity and leniency were, to a large extent, eliminated by bias adjustment. This result indicates that the bias adjustment using many-facet Rasch analysis is a viable way to control rater bias.