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 the upper half of the column by rank, giving a balanced (~50/50) split that is robust to ties (useful for coarse Likert items where a median split is badly unbalanced).

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