calcScpValues: Calculate screening cut point values for scp()

In rADA: Statistical Analysis and Cut-Point Determination of Immunoassays

Description

This function calculates the values needed for the output of the scp() data.frame

Usage

calcScpValues(
  assay.values,
  conf.level = 0.95,
  distrib = c("nonparametric", "normal"),
  transf.method = c("log10", "ln")
)

Arguments

assay.values	List of selected values from the assay data.frame such as selected values from assayMelt()
conf.level	Decimal describing level of confidence to be used for confidence interval calculation. Defaults to 0.95
distrib	Distribution selection to determine the cut point calculation. Two options: 'nonparametric' or 'normal'
transf.method	Transformation method used. The inverse will be calculated as part of the output.

Value

A data.frame cotaining the values: "mean", "sd", "distrib", "cp", "mean.conf.int1", "mean.conf.int2", "cp.conf.int1", "cp.conf.int2"

Author(s)

Emma Gail

Examples

assay.df.melted <- assayMelt(assay.df = lognormAssay, exp.name = 'Experiment1')
assay.values <- assay.df.melted[assay.df.melted$DayOperator == 'D1Op1',]$value
#This function assumes that the data has already been transformed.
scp.df <- calcScpValues(assay.values = log10(assay.values), distrib = 'normal',
transf.method = 'log10')

rADA documentation built on March 24, 2021, 1:09 a.m.