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Extract Best Cutoff and Add Binary Variable to Data Frame

Source: R/best_cutoff.R
best_cutoff.Rd

Determines the optimal cutoff point for a continuous variable in survival analysis using the maximally selected rank statistics method. Creates a binary variable based on the identified cutoff and adds it to the input data frame.

Usage

best_cutoff(
  pdata,
  variable,
  time = "time",
  status = "status",
  print_result = TRUE
)

Arguments

pdata

Data frame containing survival information and the continuous variable.

variable

Character string specifying the name of the continuous variable for which the optimal cutoff should be determined.

time

Character string specifying the column name containing time-to-event data. Default is `"time"`.

status

Character string specifying the column name containing event status (censoring information). Default is `"status"`.

print_result

Logical indicating whether to print detailed results including cutoff value and Cox model summaries. Default is `TRUE`.

Value

Data frame identical to `pdata` with an additional binary column named `<variable>_binary` containing "High" and "Low" categories based on the optimal cutoff.

Author

Dongqiang Zeng

Examples

set.seed(123)
pdata <- data.frame(
  time = rexp(100),
  status = rbinom(100, 1, 0.5),
  score = rnorm(100, mean = 50, sd = 10)
)
result <- best_cutoff(pdata, variable = "score", print_result = FALSE)
#> ✔ Best cutoff for "score": 46.503
table(result$score_binary)
#> 
#>  Low High 
#>   45   55