The intended use of this package is to implement variance functions proposed in Sadler's VFP stand-alone software
(see reference below), from which the name was borrowed as well.
Main function of this package is fit.vfp for fitting non-linear variance-function
models. Usually, these models are fitted to analysis-results of precision performance data e.g.
frequently generated for in-vitro diagnostics (IVD). R-package VFP is designed to work best on objects
of class 'VCA' as generated by R-package VCA but it is not restricted to these.
There are several functions operating on S3-objects of class 'VFP', e.g. plot.VFP,
print.VFP, summary.VFP, and predict.VFP. Function predictMean
is of special interest when a functional relationship is used to derive limit of quantitation (LoQ) or functional
sensitivity, as the concentration at which the IVD-imprecision expressed as coefficient of variation (CV) undercuts
a specific threshold.
Andre Schuetzenmeister andre.schuetzenmeister@roche.com, Florian Dufey florian.dufey@roche.com, Andrea Geistanger andrea.geistanger@roche.com
| Package: | VFP |
| Type: | Package |
| Version: | 1.4.3 |
| Date: | 2025-01-27 |
| License: | GPL (>=3) |
| LazyLoad: | yes |
CLSI EP05-A3: Evaluation of Precision of Quantitative Measurement Procedures; Approved Guideline - Third Edition. (2014)
Sadler WA, Smith MH. Use and Abuse of Imprecision Profiles: Some Pitfalls Illustarted by Computing and Plotting Confidence Intervals. Clin Chem 1990; 36/7:1346-1350
Sadler WA, Smith MH. A reliable method of estimating the variance function in immunoassays. Comput Stat Data Anal 1986; 3:227-239
Sadler WA, Smith MH. Estimation of imprecision in immunoassays quality assessment programmes. Ann Clin Biochem 1987; 24:98-102
www.aacb.asn.au/AACB/Resources/Variance-Function-Program