Brendan Scientific
Immunoassay Components
Statistical QC Links
  Smart QC
  Assay Troubleshooting
  Case Study
  Applications
  Control Parameters
  Regulatory Compliance
  Quality Assurance
  Graphs and Charts
  Demo button
top content border
Statistical QC Title
 

Case Study: Statistical Assay Analysis

StatLIA's statistical analysis and the Shewart 22S control rule were used to analyze the results of more than 1600 assays performed in a high-volume reference laboratory in the Midwest.  StatLIA's statistical analysis flagged 43 assays, compared to 15 assays flagged by the multi-rule method.  In 17 of the 43 StatLIA-flagged assays, the amount of error shifted the results of the unknowns enough to change the diagnostic interpretation. Only 4 of these failed assays were detected by the multi-rule method.  The other 11 assays of the total 15 flagged by the multi-rule method were due to bad control specimens, not bad assays, a distinction easily determined using StatLIA’s statistical analysis.

Applications


list-bullet
Characterize performance of standard curve by monitoring more than 50 standard curve parameters, including standard responses, min/max detectable concentrations, curve fit statistics, control responses and concentrations
list-bullet
Troubleshoot assays immediately and document the failed component (antibody, tracer, etc.)
list-bullet
Develop, characterize, and validate new tests
list-bullet
Establish test verification standards in StatLIA, and then monitor them automatically
list-bullet
Distinguish between a bad assay or just a bad control
list-bullet
Document and justify why a standard curve was edited
list-bullet
Generate Quality Assurance reports to verify the performance consistency of a test over time
list-bullet
Monitor Levey-Jennings Charts that plot response, normalized response, and concentration for each control
list-bullet
Analyze assay performance by verifying accuracy, precision, reportable range, specificity, reliability
list-bullet
Optimize assay performance with a complete statistical comparison of one or more assays to a stable pool of historical reference assays
list-bullet
Compare each sample’s observed variance to its predicted variance based on the variances from the test’s historical reference assays, and compute a Precision Probability based on that comparison
list-bullet
Calculate matrix effects by computing the analysis of variance for both the standards and the unknowns

Previous
Smart QC  
Previous
Up Arrow
 
Next Arrow
 
Next Arrow
 
Next Arrow
 
Next Arrow
 
Next Arrow
Top of page  
bottom border

Copyright © 2013 Brendan Technologies, Inc.
 

jordan 3 sport blue sport blue 6s retro jordans for sale sport blue 3s jordan 3 sport blue lebron 12 louis vuitton outlet cheap jordans retro jordans for sale kate spade outlet wolf grey 3s sport blue 3s Sport blue 14s louis vuitton outlet coach outlet wolf grey 3s sport blue 3s michael kors outlet sport blue 3s louis vuitton outlet michael kors outlet online retro jordans for sale sport blue 6s sport blue 3s sport blue 3s sport blue 3s cheap air jordans louis vuitton outlet coach outlet online foamposites for sale louis vuitton outlet coach outlet Louis Vuitton Outlet michael kors outlet sport blue 6s michael kors uk louis vuitton outlet michael kors outlet michael kors outlet louis vuitton outlet online