evalNorm: Normality Evaluation

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

Description

This function evaluates the normality of the melted immunoassay dataset. In order to determine whether or not the distribution is normal, two tests are performed: the Shapiro Wilk test for normality and the test for skewness. See shapiro.test and skewness for details. In order to for a "nonparametric" recommendation to be made, the SW test must be significant (below desire value) and the absolute value skewness must be above the desired value. If only one or neither of these conditions are met, then the recommendation will be "normal".

Usage

evalNorm(
  assay.obj,
  category = NULL,
  data.transf = FALSE,
  transf.method = c("log10", "ln"),
  excl.outliers = FALSE,
  hist = TRUE,
  p.val = 0.05,
  skew = 1,
  return.object = TRUE
)

Arguments

assay.obj	An ImmunoAssay object imported by importAssay
category	If assay.df.melted consists of more than 1 dataset, choose the category here to split dataset
data.transf	Should the data should be transformed before normality is evaluated
transf.method	If data.transf is TRUE, which method should be used. Can choose between 'log10' and 'ln'.
excl.outliers	Should outliers be excluded from this analysis? If TRUE, data points which lie beyond the extremes of the whiskers in boxplot will be excluded, see boxplot.stats for details.
hist	Should a histogram be outputted? TRUE/FALSE
p.val	Value to be used for cutoff for Shapiro-Wilks test. Defaults to 0.05.
skew	Value to be used to determine skewness. Defaults to 1.
return.object	If FALSE, only the plot is returned and the stats are returned as a list.

Value

If return.object==FALSE, only the plot is returned and the stats are returned as a list. Otherwise, an object of the class ImmunoAssay is returned.

Author(s)

Emma Gail

Examples

assay.obj <- importAssay(lognormAssay, exp.name = 'Experiment1')
assay.obj <- evalNorm(assay.obj, category = 'Experiment1',
data.transf = TRUE, transf.method = 'log10')

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