Clinical Chemistry AACC Online Job Center
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Clinical Chemistry 27: 1536-1545, 1981;
This Article
Right arrow Full Text (PDF)
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Westgard, J. O.
Right arrow Articles by Groth, T.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Westgard, J. O.
Right arrow Articles by Groth, T.

Clinical Chemistry, Vol 27, 1536-1545, Copyright © 1981 by American Association for Clinical Chemistry

Design and evaluation of statistical control procedures: applications of a computer "quality control simulator" program

JO Westgard and T Groth

A computer simulation program has been developed to aid in designing and evaluating statistical control procedures. This "QC stimulator" (quality control) program permits the user to study the effects of different factors on the performance of quality-control procedures. These factors may be properties of the analytical procedure, characteristics of the instrument system, or conditions for the quality- control procedure. The performance of a control procedure is characterized by its probability for rejection, as estimated at several different magnitudes of random and systematic error. These performance characteristics are presented graphically by power functions-plots of the probability for rejection vs the size of the analytical errors. The utility of this stimulation tool is illustrated by application to multi- rule single-value procedures, mean and range procedures, and a trend analysis procedure. Careful choice of control rules is necessary to minimize false rejections and to optimize error detection with multi- rule procedures. Control limits must be carefully calculated for optimum performance of mean and range procedures. The level of significance for testing control must be carefully selected for the trend analysis procedure.


The following articles in journals at HighWire Press have cited this article:


Home page
 Clin. Chem.Home page
J. O. Westgard and B. Stein
Automated Selection of Statistical Quality-Control Procedures to Assure Meeting Clinical or Analytical Quality Requirements
Clin. Chem., February 1, 1997; 43(2): 400 - 403.
[Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 1981 by the American Association for Clinical Chemistry.