A general method of determining efficiency-robust estimation and testing methods is presented. This is used to deriveadmissible linear unbiased estimators(ALUEs) having the following optimality property: Over a specified (finite) family of possible symmetric shapes of the error distribution, the estimator's respective variances cannot be jointly improved. Such estimators are generalizations of Lloyd's best linear unbiased estimators (BLUEs) determined for single shapes. Simple illustrative examples are given. Other applications of the method to estimation and testing problems are discussed briefly.