tie_binarize: Binarize continous data

In mytalbot/tiefightR: Calculate Preference Positions

Description

Uses tie_import non-binary outcome data as input. The outcome variable is randomized for ties in the continous data.

Usage

tie_binarize(
  xdata = NULL,
  RF = NULL,
  CF = NULL,
  id = NULL,
  RV = NULL,
  datalabel = "binarized",
  compiled_studies = NULL,
  setseed = TRUE,
  prefLimit = 50,
  refval = "refValue",
  oval = "otherValue",
  aid = "animalID",
  fldrnk = "fluid_drunk"
)

Arguments

xdata	imported (binarized) data frame
RF	name of the reference fluid variable
CF	name of the combination fluid variable
id	subject IDs
RV	name of the response variable
datalabel	universal study label for the binarized data
compiled_studies	label of the compiled sub study (used for filtering)
setseed	TRUE/FALSE for seeding
prefLimit	preference limit for binarization threshold
refval	the name of the standardized reference variable in the org data
oval	the name of the standardized combination variable in the org data
aid	the name of the standardized animal id column in the org data
fldrnk	the name of the standardizedresponse variable in the org data

Value

binarized data in the default format (colum headers)

mytalbot/tiefightR documentation built on July 16, 2020, 5:44 p.m.