An Analysis of Multirules for Monitoring Assay Quality Control.
Background Multirules are often employed to monitor quality control (QC). The performance of multirules is usually determined by simulation and is difficult to predict. Previous studies have not provided computer code that would enable one to experiment with multirules. It would be helpful for analy...
| Publicado en: | Laboratory Medicine Vol. 51; no. 1; pp. 94 - 99 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Feb2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Background Multirules are often employed to monitor quality control (QC). The performance of multirules is usually determined by simulation and is difficult to predict. Previous studies have not provided computer code that would enable one to experiment with multirules. It would be helpful for analysts to have computer code to analyze rule performance. Objective To provide code to calculate power curves and to investigate certain properties of multirule QC. Methods We developed computer code in the R language to simulate multirule performance. Using simulation, we studied the incremental performance of each rule and determined the average run length and time to signal. Results We provide R code for simulating multirule performance. We also provide a Microsoft Excel spreadsheet with a tabulation of results that can be used to create power curves. We found that the R4S and 10x rules add very little power to a multirule set designed to detect shifts in the mean. Conclusion QC analysts should consider using a limited-rule set. |
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