  The Reverse Stein Effect is identified and illustrated: A statistician who
shrinks his/her data toward a point chosen without reliable knowledge about the
underlying value of the parameter to be estimated but based instead upon the
observed data will not be protected by the minimax property of shrinkage
estimators such as that of James and Stein, but instead will likely incur a
greater error than if shrinkage were not used.
