loq_interval: Limits of quantifications estimation using interval method

Description Usage Arguments Details Value References Examples

View source: R/loq_interval.R

Description

Estimates the limits of quantification based on the asymptotes coefficients.

Usage

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loq_interval(x, subset.list = NULL, low.asymp = NULL, high.asymp = NULL,
    lowci = -Inf, highci = Inf, inter.method = "prediction", level = 0.95)

Arguments

x

a scluminex object

subset.list

list of analytes to estimate. Default NULL (all analytes of the scluminex object)

low.asymp

a number or character specifying the low asymptote coefficient in the model. Default NULL assumes LLOQ is the minimum value of the concentration variable.

high.asymp

a number or character specifying the high asymptote coefficient. Default NULL assumes HLOQ is the maximum value of the concentration variable

lowci

specify the lowest limit if exists for asymptote, only applies if low.asymp equals !NULL.

highci

specify the highest limit if exists for asymptote, only applies if high.asymp equals !NULL.

inter.method

interval method for estimating interval LOQ ('prediction' or 'confidence')

level

0 to 1 value specifying level of confidence. Default 0.95.

Details

If low.asymp (high.asymp) is specified lowci (highci) must be -Inf (Inf). When lowci (highci) is specified asymptote argument must be NULL. When low.asymp and lowci arguments are the default values, the funtion assumes that LOQs are maximum and minimum values of data. If low.asymp (high.asymp) or lowci (highci) arguments are specified but it is not possible to estimate the LOQ (e.g., coefficient position is not well specified or estimated values are beyond observed data) the function estimates the LOQs based on maximum and minimum values. When the background method is the constraint one, the LLOQ is the concentration value of the log10(Background MFI mean) and low.asymp and lowci doesn't apply.

Value

Object of class loq.

References

Quinn CP, Semenova VA, Elie CM et al. (2002). Specific, Sensitive, and Quantitative Enzyme-Linked Immunosorbent Assay for Human Immunoglobulin G Antibodies to Anthrax Toxin Protective Antigen. Emerg Infect Dis 8 (10),1103-10

Examples

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# 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="SSl4",
                bkg="ignore",
                fmfi="mfi",
                verbose=FALSE)

# All default arguments
loq_interval(igmodels)

# Low asymptote coefficient of the model is 2
loq_interval(igmodels, low.asymp = 2)

# Low asymptote coefficient of the model is 2 and high is 3
loq_interval(igmodels, low.asymp = 2, high.asymp = 3)

# Fix to 2 and 3 the lower and upper asymptote
loq_interval(igmodels, lowci=2, highci=3)

drLumi documentation built on May 2, 2019, 2:45 p.m.

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