In this paper, the performance of the Principal Component Measurement Test (PCMT) is evaluated when used for the identification of multiple biases. A serial elimination strategy is implemented where a statistical test based on principal component analysis is used to identify the measurement to eliminate. A simulation procedure involving random measurement errors and fixed gross error sizes is applied to evaluate its performance. This performance is compared with the one obtained using serial elimination using the conventional Measurement Test (MT), as it is performed in some commercial simulators. The analysis indicates that principal component tests alone, without the aid of other collective tests, do not significantly enhance the ability in identification features of this strategy, performing worse in some cases. A few cases of severe failure of this strategy are shown and a suggestion to test other strategies is offered.