Lesson 6, QC Planning for Healthcare Laboratories, WesTgard ® Quality Corporation © 1997

Lesson 6: QC Planning Tools - What are Power Function Graphs?

The performance of statistical QC procedures can be characterized by determining the probabilities of rejecting analytical runs that have different sizes of errors, as described in this lesson on Power Function Graphs. An example of the application of power functions considers Higher N QC Procedures for Immunoassays. Additional discussion is provided by FAQs for Power Function and Critical- Error Graphs.

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Objectives:

Gain an understanding of the origin of power curves.
Learn how to read a power function graph.
Learn how to determine the probabilities of false rejection and error detection.

Web materials:

Lesson: Power Function Graphs
QC planning application: higher N multirule QC procedures
FAQs about power function and critical-error graphs

Things to do:

Study the materials.
Run QC Validator Tutorial B.
Pick a test of interest and find out what the QC practice is in your laboratory?
Use the QC Validator program to display the power curve for that QC procedure.
Use the QC Validator program to help you answer the questions below.

Assessment: View the Answers

What P_fr would you expect for a 1_2s rule with N=2?
What about 1_3s with N=2?
What P_ed is expected for a systematic shift equivalent to 2s with these QC procedures?
What P_ed is expected for a random error that is a doubling of the method's SD?
How does P_fr change as N increases?
How does P_ed change as N increases?
Do you think your laboratory might have a false rejection problem?

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