transform_data_by_residual: transform_data_by_residual

In gladstone-institutes/CalcPower: Power Calculation for biological experiments

transform_data_by_residual

Description

This functions makes quantile-quanitle (qq) plots of i) raw residual values ii) log-transformed residual values iii) raw residual values after removing outliers, and iv) log-transformed residual values after removing outliers. To detect outliers, the function uses Rosner's test.

Usage

transform_data_by_residual(
  data,
  residual_values,
  response_column,
  alpha = 0.05
)

Arguments

data	Input data
residual_values	User provided residual values
response_column	Name of the variable observed by performing the experiment. ex) intensity.
alpha	numeric scalar between 0 and 1 indicating the Type I error associated with the test of outliers

Value

Quantile-quanitle (qq) plots of i) raw residual values ii) log-transformed residual values iii) raw residual values after removing outliers, and iv) log-transformed residual values

Examples

transform_data(data,"classif",c("experiment","line"),"feature1","TRUE")

gladstone-institutes/CalcPower documentation built on Jan. 3, 2023, 11:27 a.m.