The intended use of this package is to implement variance functions proposed in Sadler's VFP standalone 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.
| Package: | VFP |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2018-07-30 |
| 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
Sadler WA, http://www.aacb.asn.au/professionaldevelopment/useful-tools/variance-function-program-version-110. Accessed November 16, 2015