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Pairwise comparison is commonly used to estimate the priority values of finite alternatives with respect to a given criterion. We evaluate seven specially selected direct methods of estimating priority vectors from reciprocal pairwise comparison matrices under four effectiveness measures. A simulation experiment is designed starting with true priority vectors that represent difficult cases of "no obvious best alternative" and "two equal best alternatives". The simulation results suggest that the geometric mean method is in general the best method with the normalized column mean method as a close second best.

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