create_binomial: Creates a success/failure column for each IA based on counts.

In VWPre: Tools for Preprocessing Visual World Data

Description

create_binomial uses interest area count columns to create a success/failure column for each IA which is suitable for logistic regression. N.B.: This function will work for data with a maximum of 8 interest areas.

Usage

create_binomial(
  data,
  NoIA = NULL,
  ObsPerBin = NULL,
  ObsOverride = FALSE,
  CustomBinom = NULL
)

Arguments

data	A data table object output by either bin_prop or transform_to_elogit.
NoIA	A positive integer indicating the number of interest areas defined when creating the study.
ObsPerBin	A positive integer indicating the number of observations to use in the calculation. Typically, this will be the number of samples per bin, which can be determined with check_samples_per_bin.
ObsOverride	A logical value controlling restrictions on the value provided to ObsPerBin. Default value is FALSE.
CustomBinom	An optional parameter specifying a vector containing two integers corresponding to the interest area IDs to be combined.

Value

A data table with additional columns (the number of which depends on the number of interest areas specified) added to data.

Examples

## Not run: 
library(VWPre)
# Create binomial (success/failure) column...
df <- create_binomial(data = dat, NoIA = 4, ObsPerBin = 20)

## End(Not run)

VWPre documentation built on Nov. 30, 2020, 1:08 a.m.