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Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
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Related Experiment Video

Updated: May 24, 2026

Monochrome Multiplex Quantitative PCR Telomere Length Measurement
11:44

Monochrome Multiplex Quantitative PCR Telomere Length Measurement

Published on: March 22, 2024

Should I repeat my 1:2s QC rejection?

Curtis A Parvin1, Lakshmi Kuchipudi, John C Yundt-Pacheco

  • 1Bio-Rad Laboratories, Quality Systems Division, Plano, TX 75074, USA. curtis_parvin@bio-rad.com

Clinical Chemistry
|February 24, 2012
PubMed
Summary

Repeating quality control (QC) outside 2SD (1:2s rule) is common but unevaluated. This study shows repeat-sampling strategies are effective, offering power comparable to 1:2s and 1:3s QC rules with modest increases in control testing.

Area of Science:

  • Clinical Chemistry
  • Laboratory Quality Control

Background:

  • Repeating quality control (QC) samples outside 2 standard deviations (1:2s rule) is a frequent practice.
  • Despite its common use, the statistical power of this repeat-sampling approach has not been rigorously evaluated.

Purpose of the Study:

  • To mathematically and computationally evaluate the power of 1:2s repeat-sampling strategies.
  • To compare the effectiveness of these strategies against established QC rules (1:2s, 1:3s) and common multirules.

Main Methods:

  • Power functions were computed using mathematical calculations and computer simulations.
  • Four distinct 1:2s repeat-sampling strategies were analyzed.
  • Performance was benchmarked against the 1:2s rule, 1:3s rule, and two common QC multirules.

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Main Results:

  • Repeat-sampling strategies demonstrated low false-rejection rates, similar to the 1:3s QC rule.
  • Error detection rates for repeat-sampling approached those of the 1:2s rule for significant errors.
  • The power of repeat-sampling strategies generally exceeded that of the evaluated QC multirules, with a 4-13% increase in QC utilization.

Conclusions:

  • Repeat-sampling strategies effectively combine the benefits of 1:2s and 1:3s QC rules.
  • These strategies offer favorable power compared to common QC multirules.
  • The enhanced performance is achieved with a minor increase in the average number of controls tested.