Abstract

The Monte Carlo method was used to investigate the capacity of PT schemes to detect laboratories which biases are out of control. Probabilities that the computed z values are over 3 while the true value is less than 2 and that the computed z values are less than 2 while the true values are over 3 are computed for a series of situations: number of participants from 5 to 30, various ratios of repeatability over reproducibility and number of test results per participant, introduction or not of outliers with k from 3.5 to 10. For each situation, the probabilities of not detecting true outliers and to trigger false alerts are discussed. Guidance and keys are proposed to check and improve the efficiency of real PT programs.

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