Dichotomize numeric columns to 0/1

Splits each column of a numeric matrix or data frame into a binary 0/1 variable. This is the usual preprocessing step before fitting an Ising network (ising_fit(), ising_sampler()) to Likert or other ordinal/continuous data, which require binary input.

Usage

dichotomize(data, method = c("median", "mean", "rank"))

Arguments

data

Numeric matrix or data frame (rows = observations).

method

Split rule, applied independently to each column:

"median"

(default) 1 if the value is >= the column median.

"mean"

1 if the value is > the column mean.

"rank"

1 for observations whose average rank is above the midpoint. Tied values always remain together, so the split may be unbalanced rather than depending on row order.

Value

An integer matrix of 0/1 values with the same dimensions and dimnames as data.

Examples

b <- dichotomize(SRL_GPT, method = "median")
table(b)                          # values are 0/1 only
#> b
#>   0   1 
#> 694 806