evalNorm {rADA}

Normality Evaluation

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')