Description Usage Arguments Details Value References Examples
Estimates the limits of quantification based on an approximation of the coefficient of variation.
1 |
x |
a |
subset.list |
list of analytes to estimate.
Default |
max.cv |
is the target coeficient of variation by default 0.2 |
n.cuts |
is the number of cuts to search the coefficent of variation. Default 100. |
For each value of the response, the estimated concentration
value and the approximated standard deviation is estimated.
The function invest
with the delta method approach is used.
The coefficient of variation of the log10 concentration is calculated as the
√{e^{ (SE \times log(10))^2} - 1 }
Object of class loq
.
Gottschalk PG, and Dunn JR. (2005). Determining the error of dose estimates and minimum and maximum acceptable concentrations from assays with nonlinear dose-response curves. Comput Methods Programs Biomed 80, 204-215.
Defawe OD, Fong Y, Vasilyeva E, Pickett M, Carter DK, Gabriel E, Rerks-Ngarm S, Nityaphan S, Frahm N, McElrath MJ and De Rosa SC.(2012). Optimization and qualification of a multiplex bead array to assess cytokine and chemokine production by vaccine-specific cells. J Immunol Methods 382, 117-128.
1 2 3 4 5 6 7 8 9 10 11 12 | # Load data and estimate models
data(ecdata)
data(mfidata)
dat <- mfidata[mfidata$plate=="plate_1" & mfidata$analyte=="FGF",]
sdf <- data_selection(dat, ecdata)$plate_1
igmodels <- scluminex("plate_1",sdf$standard, sdf$background,
lfct=c("SSl4", "SSl5"), bkg="ignore", fmfi="mfi", verbose=FALSE)
loq_cv(igmodels, max.cv=0.25, n.cuts=100)
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