A method is presented for calculating a key comparison reference value (KCRV) and its associated standard uncertainty. The method allows for technical scrutiny of data, correction or exclusion of extreme data, but above all uses a power-moderated mean that can calculate an efficient and robust mean from any data set. For mutually consistent data, the method approaches a weighted mean, the weights being the reciprocals of the variances (squared standard uncertainties) associated with the measured values. For data sets suspected of inconsistency, the weighting is moderated by increasing the laboratory variances by a common amount and/or decreasing the power of the weighting factors. By using computer simulations, it is shown that the PMM is a good compromise between efficiency and robustness, while also providing a realistic uncertainty. The method is of particular interest to data evaluators and organizers of proficiency tests.